{"meta": {"count": 25428, "db_response_time_ms": 355, "page": 1, "per_page": 25, "groups_count": null, "x_query": {"oql": "works where full text has (Conditional Random Fields Probabilistic Models for Segmenting \"and\" Labeling Sequence Data)", "oqo": {"get_rows": "works", "filter_rows": [{"column_id": "fulltext.search", "value": "Conditional Random Fields Probabilistic Models for Segmenting and Labeling Sequence Data", "operator": "has"}]}, "url": "/works?filter=fulltext.search:Conditional Random Fields Probabilistic Models for Segmenting and Labeling Sequence Data"}, "cost_usd": 0.001}, "results": [{"id": "https://openalex.org/W2147880316", "doi": null, "title": "Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data", "display_name": "Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data", "relevance_score": 36893.957, "publication_year": 2001, "publication_date": "2001-06-28", "ids": {"openalex": "https://openalex.org/W2147880316", "mag": "2147880316"}, "language": "en", "primary_location": {"id": "pmh:oai:repository.upenn.edu:20.500.14332/6188", "is_oa": false, "landing_page_url": "https://repository.upenn.edu/handle/20.500.14332/6188", "pdf_url": null, "source": {"id": "https://openalex.org/S4306402083", "display_name": "ScholarlyCommons (University of Pennsylvania)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I79576946", "host_organization_name": "University of Pennsylvania", "host_organization_lineage": ["https://openalex.org/I79576946"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "published", "raw_type": "Presentation"}, "type": "other", "indexed_in": [], "open_access": {"is_oa": true, "oa_status": "green", "oa_url": "https://repository.upenn.edu/cis_papers/159", "any_repository_has_fulltext": true}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5060219657", "display_name": "John Lafferty", "orcid": "https://orcid.org/0000-0002-5929-220X"}, "institutions": [{"id": "https://openalex.org/I74973139", "display_name": "Carnegie Mellon University", "ror": "https://ror.org/05x2bcf33", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I74973139"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "John Lafferty", "raw_affiliation_strings": ["Carnegie Mellon University"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Carnegie Mellon University", "institution_ids": ["https://openalex.org/I74973139"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5107835063", "display_name": "Andrew McCallum", "orcid": null}, "institutions": [], "countries": [], "is_corresponding": false, "raw_author_name": "Andrew McCallum", "raw_affiliation_strings": [], "raw_orcid": null, "affiliations": []}, {"author_position": "last", "author": {"id": "https://openalex.org/A5103620421", "display_name": "Fernando C. N. Pereira", "orcid": null}, "institutions": [], "countries": [], "is_corresponding": false, "raw_author_name": "Fernando C. N. Pereira", "raw_affiliation_strings": [], "raw_orcid": null, "affiliations": []}], "institutions": [], "countries_distinct_count": 1, "institutions_distinct_count": 1, "corresponding_author_ids": [], "corresponding_institution_ids": [], "apc_list": null, "apc_paid": null, "fwci": null, "has_fulltext": true, "cited_by_count": 13013, "citation_normalized_percentile": null, "cited_by_percentile_year": null, "biblio": {"volume": null, "issue": null, "first_page": "282", "last_page": "289"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 0.9995999932289124, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 0.9995999932289124, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T11269", "display_name": "Algorithms and Data Compression", "score": 0.9994999766349792, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10201", "display_name": "Speech Recognition and Synthesis", "score": 0.9954000115394592, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/conditional-random-field", "display_name": "Conditional random field", "score": 0.8620038032531738}, {"id": "https://openalex.org/keywords/maximum-entropy-markov-model", "display_name": "Maximum-entropy Markov model", "score": 0.7686716318130493}, {"id": "https://openalex.org/keywords/graphical-model", "display_name": "Graphical model", "score": 0.7356168031692505}, {"id": "https://openalex.org/keywords/conditional-entropy", "display_name": "Conditional entropy", "score": 0.6463481783866882}, {"id": "https://openalex.org/keywords/conditional-independence", "display_name": "Conditional independence", "score": 0.6337764263153076}, {"id": "https://openalex.org/keywords/variable-order-markov-model", "display_name": "Variable-order Markov model", "score": 0.6314831376075745}, {"id": "https://openalex.org/keywords/discriminative-model", "display_name": "Discriminative model", "score": 0.6152151823043823}, {"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.579765260219574}, {"id": "https://openalex.org/keywords/random-field", "display_name": "Random field", "score": 0.5659407377243042}, {"id": "https://openalex.org/keywords/hidden-markov-model", "display_name": "Hidden Markov model", "score": 0.5446375012397766}, {"id": "https://openalex.org/keywords/probabilistic-logic", "display_name": "Probabilistic logic", "score": 0.5443957448005676}, {"id": "https://openalex.org/keywords/markov-model", "display_name": "Markov model", "score": 0.5392348766326904}, {"id": "https://openalex.org/keywords/markov-chain", "display_name": "Markov chain", "score": 0.5348206162452698}, {"id": "https://openalex.org/keywords/markov-random-field", "display_name": "Markov random field", "score": 0.4570564925670624}, {"id": "https://openalex.org/keywords/conditional-probability", "display_name": "Conditional probability", "score": 0.44316428899765015}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.4425256848335266}, {"id": "https://openalex.org/keywords/principle-of-maximum-entropy", "display_name": "Principle of maximum entropy", "score": 0.4402584433555603}, {"id": "https://openalex.org/keywords/mathematics", "display_name": "Mathematics", "score": 0.35230493545532227}, {"id": "https://openalex.org/keywords/machine-learning", "display_name": "Machine learning", "score": 0.3213096261024475}, {"id": "https://openalex.org/keywords/statistics", "display_name": "Statistics", "score": 0.1229981780052185}, {"id": "https://openalex.org/keywords/segmentation", "display_name": "Segmentation", "score": 0.09538546204566956}, {"id": "https://openalex.org/keywords/image-segmentation", "display_name": "Image segmentation", "score": 0.0811547338962555}], "concepts": [{"id": "https://openalex.org/C152565575", "wikidata": "https://www.wikidata.org/wiki/Q1124538", "display_name": "Conditional random field", "level": 2, "score": 0.8620038032531738}, {"id": "https://openalex.org/C196956702", "wikidata": "https://www.wikidata.org/wiki/Q6795829", "display_name": "Maximum-entropy Markov model", "level": 5, "score": 0.7686716318130493}, {"id": "https://openalex.org/C155846161", "wikidata": "https://www.wikidata.org/wiki/Q1143367", "display_name": "Graphical model", "level": 2, "score": 0.7356168031692505}, {"id": "https://openalex.org/C101721835", "wikidata": "https://www.wikidata.org/wiki/Q813908", "display_name": "Conditional entropy", "level": 3, "score": 0.6463481783866882}, {"id": "https://openalex.org/C79772020", "wikidata": "https://www.wikidata.org/wiki/Q5159264", "display_name": "Conditional independence", "level": 2, "score": 0.6337764263153076}, {"id": "https://openalex.org/C54907487", "wikidata": "https://www.wikidata.org/wiki/Q7915688", "display_name": "Variable-order Markov model", "level": 4, "score": 0.6314831376075745}, {"id": "https://openalex.org/C97931131", "wikidata": "https://www.wikidata.org/wiki/Q5282087", "display_name": "Discriminative model", "level": 2, "score": 0.6152151823043823}, {"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.579765260219574}, {"id": "https://openalex.org/C130402806", "wikidata": "https://www.wikidata.org/wiki/Q5361768", "display_name": "Random field", "level": 2, "score": 0.5659407377243042}, {"id": "https://openalex.org/C23224414", "wikidata": "https://www.wikidata.org/wiki/Q176769", "display_name": "Hidden Markov model", "level": 2, "score": 0.5446375012397766}, {"id": "https://openalex.org/C49937458", "wikidata": "https://www.wikidata.org/wiki/Q2599292", "display_name": "Probabilistic logic", "level": 2, "score": 0.5443957448005676}, {"id": "https://openalex.org/C163836022", "wikidata": "https://www.wikidata.org/wiki/Q6771326", "display_name": "Markov model", "level": 3, "score": 0.5392348766326904}, {"id": "https://openalex.org/C98763669", "wikidata": "https://www.wikidata.org/wiki/Q176645", "display_name": "Markov chain", "level": 2, "score": 0.5348206162452698}, {"id": "https://openalex.org/C2778045648", "wikidata": "https://www.wikidata.org/wiki/Q176827", "display_name": "Markov random field", "level": 4, "score": 0.4570564925670624}, {"id": "https://openalex.org/C44492722", "wikidata": "https://www.wikidata.org/wiki/Q327069", "display_name": "Conditional probability", "level": 2, "score": 0.44316428899765015}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.4425256848335266}, {"id": "https://openalex.org/C9679016", "wikidata": "https://www.wikidata.org/wiki/Q1417473", "display_name": "Principle of maximum entropy", "level": 2, "score": 0.4402584433555603}, {"id": "https://openalex.org/C33923547", "wikidata": "https://www.wikidata.org/wiki/Q395", "display_name": "Mathematics", "level": 0, "score": 0.35230493545532227}, {"id": "https://openalex.org/C119857082", "wikidata": "https://www.wikidata.org/wiki/Q2539", "display_name": "Machine learning", "level": 1, "score": 0.3213096261024475}, {"id": "https://openalex.org/C105795698", "wikidata": "https://www.wikidata.org/wiki/Q12483", "display_name": "Statistics", "level": 1, "score": 0.1229981780052185}, {"id": "https://openalex.org/C89600930", "wikidata": "https://www.wikidata.org/wiki/Q1423946", "display_name": "Segmentation", "level": 2, "score": 0.09538546204566956}, {"id": "https://openalex.org/C124504099", "wikidata": "https://www.wikidata.org/wiki/Q56933", "display_name": "Image segmentation", "level": 3, "score": 0.0811547338962555}], "mesh": [], "locations_count": 13, "locations": [{"id": "pmh:oai:repository.upenn.edu:20.500.14332/6188", "is_oa": false, "landing_page_url": "https://repository.upenn.edu/handle/20.500.14332/6188", "pdf_url": null, "source": {"id": "https://openalex.org/S4306402083", "display_name": "ScholarlyCommons (University of Pennsylvania)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I79576946", "host_organization_name": "University of Pennsylvania", "host_organization_lineage": ["https://openalex.org/I79576946"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "published", "raw_type": "Presentation"}, {"id": "pmh:oai:repository.upenn.edu:cis_papers-1162", "is_oa": true, "landing_page_url": "https://repository.upenn.edu/cis_papers/159", "pdf_url": "https://repository.upenn.edu/cis_papers/159", "source": {"id": "https://openalex.org/S4306402083", "display_name": "ScholarlyCommons (University of Pennsylvania)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I79576946", "host_organization_name": "University of Pennsylvania", "host_organization_lineage": ["https://openalex.org/I79576946"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Departmental Papers (CIS)", "raw_type": "text"}, {"id": "pmh:oai:works.bepress.com:andrew_mccallum-1003", "is_oa": true, "landing_page_url": "https://works.bepress.com/andrew_mccallum/4", "pdf_url": "https://works.bepress.com/andrew_mccallum/4", "source": {"id": "https://openalex.org/S4306402057", "display_name": "Scholarworks (University of Massachusetts Amherst)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I24603500", "host_organization_name": "University of Massachusetts Amherst", "host_organization_lineage": ["https://openalex.org/I24603500"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Andrew McCallum", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.120.9821", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.120.9821", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.seas.upenn.edu/~strctlrn/bib/PDF/crf.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.178.3657", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.178.3657", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.18.9824", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.18.9824", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.aladdin.cs.cmu.edu/papers/pdfs/y2001/crf.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.21.695", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.21.695", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cs.cmu.edu/~mccallum/papers/crf-icml01.ps.gz", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.29.2604", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.29.2604", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cs.cmu.edu/afs/cs/project/link-3/lafferty/www/ps/crf.ps", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.296.308", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.296.308", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cs.columbia.edu/~jebara/6772/papers/crf.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.305.837", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.305.837", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.508.4217", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.508.4217", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.facweb.iitkgp.ernet.in/~sudeshna/courses/ml08/crf-lafferty-mccallum.pdf", "raw_type": "text"}, {"id": "mag:2147880316", "is_oa": false, "landing_page_url": "http://axon.cs.byu.edu/Dan/778/papers/Markov%20Random%20Fields/lafferty*.pdf", "pdf_url": null, "source": {"id": "https://openalex.org/S4306419644", "display_name": "International Conference on Machine Learning", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": null, "host_organization_name": null, "host_organization_lineage": [], "host_organization_lineage_names": [], "type": "conference"}, "license": null, "license_id": null, "version": null, "is_accepted": false, "is_published": null, "raw_source_name": "International Conference on Machine Learning", "raw_type": null}, {"id": "mag:3137935178", "is_oa": false, "landing_page_url": "https://repositorio.leon.uia.mx/xmlui/handle/20.500.12152/52539", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": null, "is_accepted": false, "is_published": null, "raw_source_name": null, "raw_type": null}], "best_oa_location": {"id": "pmh:oai:repository.upenn.edu:cis_papers-1162", "is_oa": true, "landing_page_url": "https://repository.upenn.edu/cis_papers/159", "pdf_url": "https://repository.upenn.edu/cis_papers/159", "source": {"id": "https://openalex.org/S4306402083", "display_name": "ScholarlyCommons (University of Pennsylvania)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I79576946", "host_organization_name": "University of Pennsylvania", "host_organization_lineage": ["https://openalex.org/I79576946"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Departmental Papers (CIS)", "raw_type": "text"}, "sustainable_development_goals": [{"display_name": "Reduced inequalities", "score": 0.7599999904632568, "id": "https://metadata.un.org/sdg/10"}], "awards": [], "funders": [], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2147880316.pdf", "grobid_xml": "https://content.openalex.org/works/W2147880316.grobid-xml"}, "referenced_works_count": 24, "referenced_works": ["https://openalex.org/W177913229", "https://openalex.org/W1529196404", "https://openalex.org/W1546961578", "https://openalex.org/W1574901103", "https://openalex.org/W1597379537", "https://openalex.org/W1749358154", "https://openalex.org/W1773803948", "https://openalex.org/W1934019294", "https://openalex.org/W1987458394", "https://openalex.org/W1988790447", "https://openalex.org/W2001792610", "https://openalex.org/W2009570821", "https://openalex.org/W2013714680", "https://openalex.org/W2022951240", "https://openalex.org/W2096175520", "https://openalex.org/W2117400858", "https://openalex.org/W2125529971", "https://openalex.org/W2145948275", "https://openalex.org/W2151457493", "https://openalex.org/W2160842254", "https://openalex.org/W2161290181", "https://openalex.org/W2310919327", "https://openalex.org/W2994982620", "https://openalex.org/W3021452258"], "related_works": ["https://openalex.org/W2964121744", "https://openalex.org/W2963341956", "https://openalex.org/W2962902328", "https://openalex.org/W2296283641", "https://openalex.org/W2250539671", "https://openalex.org/W2158899491", "https://openalex.org/W2156515921", "https://openalex.org/W2153579005", "https://openalex.org/W2144578941", "https://openalex.org/W2141099517", "https://openalex.org/W2125838338", "https://openalex.org/W2105644991", "https://openalex.org/W2096765155", "https://openalex.org/W2096175520", "https://openalex.org/W2064675550", "https://openalex.org/W2008652694", "https://openalex.org/W1940872118", "https://openalex.org/W1934019294", "https://openalex.org/W1766290689", "https://openalex.org/W1632114991"], "abstract_inverted_index": {"We": [0, 67], "present": [1, 68], "Conditional": [2, 15, 38], "Random": [3], "Fields,": [4], "a": [5], "framework&#13;\\nfor": [6], "building": [7], "probabilistic": [8], "models": [9, 22, 48, 53, 81], "to": [10, 31, 82], "segment&#13;\\nand": [11], "label": [12], "sequence": [13], "data.": [14, 89], "random&#13;\\nfields": [16], "offer": [17], "several": [18], "advantages": [19], "over": [20], "hidden&#13;\\nMarkov": [21], "and": [23, 50, 75, 84, 87], "stochastic": [24], "grammars&#13;\\nfor": [25], "such": [26], "tasks,": [27], "including": [28], "the": [29, 77], "ability": [30], "relax&#13;\\nstrong": [32], "independence": [33], "assumptions": [34], "made": [35], "in": [36], "those&#13;\\nmodels.": [37], "random": [39], "fields": [40, 74], "also": [41], "avoid&#13;\\na": [42], "fundamental": [43], "limitation": [44], "of": [45], "maximum": [46], "entropy&#13;\\nMarkov": [47], "(MEMMs)": [49], "other": [51], "discriminative&#13;\\nMarkov": [52], "based": [54], "on": [55], "directed": [56], "graphical&#13;\\nmodels,": [57], "which": [58], "can": [59], "be": [60], "biased": [61], "towards": [62], "states&#13;\\nwith": [63], "few": [64], "successor": [65], "states.": [66], "iterative&#13;\\nparameter": [69], "estimation": [70], "algorithms": [71], "for": [72], "conditional&#13;\\nrandom": [73], "compare": [76], "performance": [78], "of&#13;\\nthe": [79], "resulting": [80], "HMMs": [83], "MEMMs": [85], "on&#13;\\nsynthetic": [86], "natural-language": [88]}, "counts_by_year": [{"year": 2025, "cited_by_count": 98}, {"year": 2024, "cited_by_count": 166}, {"year": 2023, "cited_by_count": 394}, {"year": 2022, "cited_by_count": 457}, {"year": 2021, "cited_by_count": 823}, {"year": 2020, "cited_by_count": 888}, {"year": 2019, "cited_by_count": 909}, {"year": 2018, "cited_by_count": 873}, {"year": 2017, "cited_by_count": 711}, {"year": 2016, "cited_by_count": 878}, {"year": 2015, "cited_by_count": 856}, {"year": 2014, "cited_by_count": 858}, {"year": 2013, "cited_by_count": 851}, {"year": 2012, "cited_by_count": 775}], "updated_date": "2026-08-04T08:18:43.703281", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W2152463966", "doi": "https://doi.org/10.1145/1015330.1015422", "title": "Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data", "display_name": "Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data", "relevance_score": 2290.9302, "publication_year": 2007, "publication_date": "2007-05-01", "ids": {"openalex": "https://openalex.org/W2152463966", "doi": "https://doi.org/10.1145/1015330.1015422", "mag": "2152463966"}, "language": "en", "primary_location": {"id": "pmh:oai:scholarworks.umass.edu:cs_faculty_pubs-1062", "is_oa": true, "landing_page_url": "https://scholarworks.umass.edu/cs_faculty_pubs/63", "pdf_url": "https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1062&context=cs_faculty_pubs", "source": {"id": "https://openalex.org/S4306402240", "display_name": "ScholarWorks@UMassAmherst (University of Massachusetts Amherst)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I24603500", "host_organization_name": "University of Massachusetts Amherst", "host_organization_lineage": ["https://openalex.org/I24603500"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Computer Science Department Faculty Publication Series", "raw_type": "text"}, "type": "article", "indexed_in": [], "open_access": {"is_oa": true, "oa_status": "green", "oa_url": "https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1062&context=cs_faculty_pubs", "any_repository_has_fulltext": true}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5028501178", "display_name": "Charles Sutton", "orcid": "https://orcid.org/0000-0002-0041-3820"}, "institutions": [], "countries": [], "is_corresponding": false, "raw_author_name": "Charles Sutton", "raw_affiliation_strings": ["School of Informatics"], "raw_orcid": "https://orcid.org/0000-0002-0041-3820", "affiliations": [{"raw_affiliation_string": "School of Informatics", "institution_ids": []}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5107835063", "display_name": "Andrew McCallum", "orcid": null}, "institutions": [], "countries": [], "is_corresponding": false, "raw_author_name": "Andrew McCallum", "raw_affiliation_strings": [], "raw_orcid": null, "affiliations": []}, {"author_position": "last", "author": {"id": "https://openalex.org/A5037673735", "display_name": "Khashayar Rohanimanesh", "orcid": null}, "institutions": [], "countries": [], "is_corresponding": false, "raw_author_name": "Khashayar Rohanimanesh", "raw_affiliation_strings": [], "raw_orcid": null, "affiliations": []}], "institutions": [], "countries_distinct_count": 0, "institutions_distinct_count": 0, "corresponding_author_ids": [], "corresponding_institution_ids": [], "apc_list": null, "apc_paid": null, "fwci": 40.9898, "has_fulltext": true, "cited_by_count": 292, "citation_normalized_percentile": {"value": 0.99781886, "is_in_top_1_percent": true, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 91, "max": 100}, "biblio": {"volume": "8", "issue": "25", "first_page": "693", "last_page": "723"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9995999932289124, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9995999932289124, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 0.9987999796867371, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T11303", "display_name": "Bayesian Modeling and Causal Inference", "score": 0.9987000226974487, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/conditional-random-field", "display_name": "Conditional random field", "score": 0.7507455348968506}, {"id": "https://openalex.org/keywords/crfs", "display_name": "CRFS", "score": 0.6815860271453857}, {"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.6349773406982422}, {"id": "https://openalex.org/keywords/sequence-labeling", "display_name": "Sequence labeling", "score": 0.6085540652275085}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.5748810172080994}, {"id": "https://openalex.org/keywords/inference", "display_name": "Inference", "score": 0.5737910270690918}, {"id": "https://openalex.org/keywords/approximate-inference", "display_name": "Approximate inference", "score": 0.5354808568954468}, {"id": "https://openalex.org/keywords/graphical-model", "display_name": "Graphical model", "score": 0.5062231421470642}, {"id": "https://openalex.org/keywords/belief-propagation", "display_name": "Belief propagation", "score": 0.5041145086288452}, {"id": "https://openalex.org/keywords/machine-learning", "display_name": "Machine learning", "score": 0.47966861724853516}, {"id": "https://openalex.org/keywords/latent-variable", "display_name": "Latent variable", "score": 0.47599613666534424}, {"id": "https://openalex.org/keywords/probabilistic-logic", "display_name": "Probabilistic logic", "score": 0.43268924951553345}, {"id": "https://openalex.org/keywords/chain-rule", "display_name": "Chain rule (probability)", "score": 0.41860175132751465}, {"id": "https://openalex.org/keywords/conditional-probability-distribution", "display_name": "Conditional probability distribution", "score": 0.41626542806625366}, {"id": "https://openalex.org/keywords/dynamic-bayesian-network", "display_name": "Dynamic Bayesian network", "score": 0.4150088429450989}, {"id": "https://openalex.org/keywords/bayesian-network", "display_name": "Bayesian network", "score": 0.3718275725841522}, {"id": "https://openalex.org/keywords/bayesian-probability", "display_name": "Bayesian probability", "score": 0.3068801164627075}, {"id": "https://openalex.org/keywords/mathematics", "display_name": "Mathematics", "score": 0.27410972118377686}, {"id": "https://openalex.org/keywords/algorithm", "display_name": "Algorithm", "score": 0.2720487713813782}, {"id": "https://openalex.org/keywords/posterior-probability", "display_name": "Posterior probability", "score": 0.26492738723754883}, {"id": "https://openalex.org/keywords/task", "display_name": "Task (project management)", "score": 0.23151510953903198}, {"id": "https://openalex.org/keywords/regular-conditional-probability", "display_name": "Regular conditional probability", "score": 0.14595523476600647}, {"id": "https://openalex.org/keywords/statistics", "display_name": "Statistics", "score": 0.11830934882164001}], "concepts": [{"id": "https://openalex.org/C152565575", "wikidata": "https://www.wikidata.org/wiki/Q1124538", "display_name": "Conditional random field", "level": 2, "score": 0.7507455348968506}, {"id": "https://openalex.org/C2775953691", "wikidata": "https://www.wikidata.org/wiki/Q5013874", "display_name": "CRFS", "level": 3, "score": 0.6815860271453857}, {"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.6349773406982422}, {"id": "https://openalex.org/C35639132", "wikidata": "https://www.wikidata.org/wiki/Q7452468", "display_name": "Sequence labeling", "level": 3, "score": 0.6085540652275085}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.5748810172080994}, {"id": "https://openalex.org/C2776214188", "wikidata": "https://www.wikidata.org/wiki/Q408386", "display_name": "Inference", "level": 2, "score": 0.5737910270690918}, {"id": "https://openalex.org/C2777472644", "wikidata": "https://www.wikidata.org/wiki/Q16968992", "display_name": "Approximate inference", "level": 3, "score": 0.5354808568954468}, {"id": "https://openalex.org/C155846161", "wikidata": "https://www.wikidata.org/wiki/Q1143367", "display_name": "Graphical model", "level": 2, "score": 0.5062231421470642}, {"id": "https://openalex.org/C152948882", "wikidata": "https://www.wikidata.org/wiki/Q4060686", "display_name": "Belief propagation", "level": 3, "score": 0.5041145086288452}, {"id": "https://openalex.org/C119857082", "wikidata": "https://www.wikidata.org/wiki/Q2539", "display_name": "Machine learning", "level": 1, "score": 0.47966861724853516}, {"id": "https://openalex.org/C51167844", "wikidata": "https://www.wikidata.org/wiki/Q4422623", "display_name": "Latent variable", "level": 2, "score": 0.47599613666534424}, {"id": "https://openalex.org/C49937458", "wikidata": "https://www.wikidata.org/wiki/Q2599292", "display_name": "Probabilistic logic", "level": 2, "score": 0.43268924951553345}, {"id": "https://openalex.org/C33825631", "wikidata": "https://www.wikidata.org/wiki/Q17004731", "display_name": "Chain rule (probability)", "level": 5, "score": 0.41860175132751465}, {"id": "https://openalex.org/C43555835", "wikidata": "https://www.wikidata.org/wiki/Q2300258", "display_name": "Conditional probability distribution", "level": 2, "score": 0.41626542806625366}, {"id": "https://openalex.org/C82142266", "wikidata": "https://www.wikidata.org/wiki/Q3456604", "display_name": "Dynamic Bayesian network", "level": 3, "score": 0.4150088429450989}, {"id": "https://openalex.org/C33724603", "wikidata": "https://www.wikidata.org/wiki/Q812540", "display_name": "Bayesian network", "level": 2, "score": 0.3718275725841522}, {"id": "https://openalex.org/C107673813", "wikidata": "https://www.wikidata.org/wiki/Q812534", "display_name": "Bayesian probability", "level": 2, "score": 0.3068801164627075}, {"id": "https://openalex.org/C33923547", "wikidata": "https://www.wikidata.org/wiki/Q395", "display_name": "Mathematics", "level": 0, "score": 0.27410972118377686}, {"id": "https://openalex.org/C11413529", "wikidata": "https://www.wikidata.org/wiki/Q8366", "display_name": "Algorithm", "level": 1, "score": 0.2720487713813782}, {"id": "https://openalex.org/C57830394", "wikidata": "https://www.wikidata.org/wiki/Q278079", "display_name": "Posterior probability", "level": 3, "score": 0.26492738723754883}, {"id": "https://openalex.org/C2780451532", "wikidata": "https://www.wikidata.org/wiki/Q759676", "display_name": "Task (project management)", "level": 2, "score": 0.23151510953903198}, {"id": "https://openalex.org/C103982235", "wikidata": "https://www.wikidata.org/wiki/Q7309594", "display_name": "Regular conditional probability", "level": 4, "score": 0.14595523476600647}, {"id": "https://openalex.org/C105795698", "wikidata": "https://www.wikidata.org/wiki/Q12483", "display_name": "Statistics", "level": 1, "score": 0.11830934882164001}, {"id": "https://openalex.org/C187736073", "wikidata": "https://www.wikidata.org/wiki/Q2920921", "display_name": "Management", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C57273362", "wikidata": "https://www.wikidata.org/wiki/Q576722", "display_name": "Decoding methods", "level": 2, "score": 0.0}, {"id": "https://openalex.org/C162324750", "wikidata": "https://www.wikidata.org/wiki/Q8134", "display_name": "Economics", "level": 0, "score": 0.0}], "mesh": [], "locations_count": 12, "locations": [{"id": "pmh:oai:scholarworks.umass.edu:cs_faculty_pubs-1062", "is_oa": true, "landing_page_url": "https://scholarworks.umass.edu/cs_faculty_pubs/63", "pdf_url": "https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1062&context=cs_faculty_pubs", "source": {"id": "https://openalex.org/S4306402240", "display_name": "ScholarWorks@UMassAmherst (University of Massachusetts Amherst)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I24603500", "host_organization_name": "University of Massachusetts Amherst", "host_organization_lineage": ["https://openalex.org/I24603500"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Computer Science Department Faculty Publication Series", "raw_type": "text"}, {"id": "pmh:oai:pure.ed.ac.uk:publications/91858f91-5ed1-49d6-9aeb-1c1a9a1e1e40", "is_oa": true, "landing_page_url": "http://doi.acm.org/10.1145/1015330.1015422", "pdf_url": "https://www.pure.ed.ac.uk/ws/files/14899616/p308_sutton.pdf", "source": {"id": "https://openalex.org/S4306400321", "display_name": "Edinburgh Research Explorer (University of Edinburgh)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I98677209", "host_organization_name": "University of Edinburgh", "host_organization_lineage": ["https://openalex.org/I98677209"], "host_organization_lineage_names": [], "type": "repository"}, "license": "other-oa", "license_id": "https://openalex.org/licenses/other-oa", "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Sutton, C, Rohanimanesh, K & McCallum, A 2004, Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data. in Proceedings of the Twenty-first International Conference on Machine Learning. New York, NY, USA. https://doi.org/10.1145/1015330.1015422", "raw_type": "contributionToPeriodical"}, {"id": "pmh:oai:pure.ed.ac.uk:publications/e2b2f5e1-e843-40e1-9d81-84868dc88185", "is_oa": true, "landing_page_url": "https://www.research.ed.ac.uk/en/publications/e2b2f5e1-e843-40e1-9d81-84868dc88185", "pdf_url": "https://www.research.ed.ac.uk/en/publications/e2b2f5e1-e843-40e1-9d81-84868dc88185", "source": {"id": "https://openalex.org/S4306400321", "display_name": "Edinburgh Research Explorer (University of Edinburgh)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I98677209", "host_organization_name": "University of Edinburgh", "host_organization_lineage": ["https://openalex.org/I98677209"], "host_organization_lineage_names": [], "type": "repository"}, "license": "other-oa", "license_id": "https://openalex.org/licenses/other-oa", "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Sutton, C, McCallum, A & Rohanimanesh, K 2007, 'Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data', Journal of Machine Learning Research, vol. 8, pp. 693-723. < http://dl.acm.org/citation.cfm?id=1248659.1248684 >", "raw_type": "info:eu-repo/semantics/publishedVersion"}, {"id": "pmh:oai:works.bepress.com:andrew_mccallum-1013", "is_oa": true, "landing_page_url": "https://works.bepress.com/andrew_mccallum/14", "pdf_url": "https://works.bepress.com/andrew_mccallum/14", "source": {"id": "https://openalex.org/S4306402240", "display_name": "ScholarWorks@UMassAmherst (University of Massachusetts Amherst)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I24603500", "host_organization_name": "University of Massachusetts Amherst", "host_organization_lineage": ["https://openalex.org/I24603500"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Andrew McCallum", "raw_type": "text"}, {"id": "pmh:oai:scholarworks.umass.edu:cs_faculty_pubs-1900", "is_oa": false, "landing_page_url": "https://scholarworks.umass.edu/cs_faculty_pubs/901", "pdf_url": null, "source": {"id": "https://openalex.org/S4306402240", "display_name": "ScholarWorks@UMassAmherst (University of Massachusetts Amherst)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I24603500", "host_organization_name": "University of Massachusetts Amherst", "host_organization_lineage": ["https://openalex.org/I24603500"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Computer Science Department Faculty Publication Series", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.2.4799", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.2.4799", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.aicml.cs.ualberta.ca/banff04/icml/pages/papers/308.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.6.1707", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.6.1707", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://ciir.cs.umass.edu/pubfiles/ir-348.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.93.3930", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.93.3930", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cs.umass.edu/~mccallum/papers/dcrf-jmlr2007.pdf", "raw_type": "text"}, {"id": "pmh:oai:pure.ed.ac.uk:openaire/91858f91-5ed1-49d6-9aeb-1c1a9a1e1e40", "is_oa": true, "landing_page_url": "https://www.research.ed.ac.uk/en/publications/91858f91-5ed1-49d6-9aeb-1c1a9a1e1e40", "pdf_url": null, "source": {"id": "https://openalex.org/S4306400321", "display_name": "Edinburgh Research Explorer (University of Edinburgh)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I98677209", "host_organization_name": "University of Edinburgh", "host_organization_lineage": ["https://openalex.org/I98677209"], "host_organization_lineage_names": [], "type": "repository"}, "license": "other-oa", "license_id": "https://openalex.org/licenses/other-oa", "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Sutton, C, Rohanimanesh, K & McCallum, A 2004, Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data. in Proceedings of the Twenty-first International Conference on Machine Learning. New York, NY, USA. https://doi.org/10.1145/1015330.1015422", "raw_type": "contributionToPeriodical"}, {"id": "pmh:oai:scholarworks.umass.edu:20.500.14394/10246", "is_oa": false, "landing_page_url": "https://hdl.handle.net/20.500.14394/10246", "pdf_url": null, "source": {"id": "https://openalex.org/S4306402057", "display_name": "Scholarworks (University of Massachusetts Amherst)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I24603500", "host_organization_name": "University of Massachusetts Amherst", "host_organization_lineage": ["https://openalex.org/I24603500"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "published", "raw_type": "Article"}, {"id": "pmh:oai:scholarworks.umass.edu:20.500.14394/10490", "is_oa": false, "landing_page_url": "https://hdl.handle.net/20.500.14394/10490", "pdf_url": null, "source": {"id": "https://openalex.org/S4306402057", "display_name": "Scholarworks (University of Massachusetts Amherst)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I24603500", "host_organization_name": "University of Massachusetts Amherst", "host_organization_lineage": ["https://openalex.org/I24603500"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "published", "raw_type": "Article"}, {"id": "mag:2152463966", "is_oa": false, "landing_page_url": "https://www.jmlr.org/papers/volume8/sutton07a/sutton07a.pdf", "pdf_url": null, "source": {"id": "https://openalex.org/S118988714", "display_name": "Journal of Machine Learning Research", "issn_l": "1532-4435", "issn": ["1532-4435", "1533-7928"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310315718", "host_organization_name": "The MIT Press", "host_organization_lineage": ["https://openalex.org/P4310315718"], "host_organization_lineage_names": ["The MIT Press"], "type": "journal"}, "license": null, "license_id": null, "version": null, "is_accepted": false, "is_published": null, "raw_source_name": "Journal of Machine Learning Research", "raw_type": null}], "best_oa_location": {"id": "pmh:oai:scholarworks.umass.edu:cs_faculty_pubs-1062", "is_oa": true, "landing_page_url": "https://scholarworks.umass.edu/cs_faculty_pubs/63", "pdf_url": "https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1062&context=cs_faculty_pubs", "source": {"id": "https://openalex.org/S4306402240", "display_name": "ScholarWorks@UMassAmherst (University of Massachusetts Amherst)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I24603500", "host_organization_name": "University of Massachusetts Amherst", "host_organization_lineage": ["https://openalex.org/I24603500"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Computer Science Department Faculty Publication Series", "raw_type": "text"}, "sustainable_development_goals": [{"display_name": "Quality Education", "score": 0.699999988079071, "id": "https://metadata.un.org/sdg/4"}], "awards": [{"id": "https://openalex.org/G730876220", "display_name": null, "funder_award_id": "NBCHD-03-0010", "funder_id": "https://openalex.org/F4320332180", "funder_display_name": "Defense Advanced Research Projects Agency"}, {"id": "https://openalex.org/G7704502625", "display_name": "ITR:     Unified Graphical Models of Information Extraction and Data Mining with Application to Social Network Analysis", "funder_award_id": "0326249", "funder_id": "https://openalex.org/F4320306076", "funder_display_name": "National Science Foundation"}], "funders": [{"id": "https://openalex.org/F4320306076", "display_name": "National Science Foundation", "ror": "https://ror.org/021nxhr62"}, {"id": "https://openalex.org/F4320311089", "display_name": "National Security Agency", "ror": "https://ror.org/0047bvr32"}, {"id": "https://openalex.org/F4320332180", "display_name": "Defense Advanced Research Projects Agency", "ror": "https://ror.org/02caytj08"}, {"id": "https://openalex.org/F4320332815", "display_name": "Advanced Research Projects Agency", "ror": "https://ror.org/02caytj08"}], "has_content": {"grobid_xml": false, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2152463966.pdf"}, "referenced_works_count": 60, "referenced_works": ["https://openalex.org/W28412257", "https://openalex.org/W147273232", "https://openalex.org/W1499578805", "https://openalex.org/W1515272691", "https://openalex.org/W1525888637", "https://openalex.org/W1526729636", "https://openalex.org/W1528056001", "https://openalex.org/W1530235965", "https://openalex.org/W1560512119", "https://openalex.org/W1578057148", "https://openalex.org/W1601974683", "https://openalex.org/W1604803556", "https://openalex.org/W1632114991", "https://openalex.org/W1636244751", "https://openalex.org/W1732623802", "https://openalex.org/W1766290689", "https://openalex.org/W1773803948", "https://openalex.org/W1934019294", "https://openalex.org/W1988995507", "https://openalex.org/W1999595522", "https://openalex.org/W2008652694", "https://openalex.org/W2020294948", "https://openalex.org/W2034797903", "https://openalex.org/W2041522124", "https://openalex.org/W2046932483", "https://openalex.org/W2095844239", "https://openalex.org/W2096044236", "https://openalex.org/W2096071754", "https://openalex.org/W2096175520", "https://openalex.org/W2098921539", "https://openalex.org/W2102667697", "https://openalex.org/W2105644991", "https://openalex.org/W2109189215", "https://openalex.org/W2110575115", "https://openalex.org/W2114521167", "https://openalex.org/W2116064496", "https://openalex.org/W2116410915", "https://openalex.org/W2118029084", "https://openalex.org/W2125838338", "https://openalex.org/W2139686264", "https://openalex.org/W2143349571", "https://openalex.org/W2146143523", "https://openalex.org/W2147880316", "https://openalex.org/W2148160361", "https://openalex.org/W2151322733", "https://openalex.org/W2155925463", "https://openalex.org/W2156515921", "https://openalex.org/W2158823144", "https://openalex.org/W2162340487", "https://openalex.org/W2163518744", "https://openalex.org/W2163915185", "https://openalex.org/W2164450870", "https://openalex.org/W2169415915", "https://openalex.org/W2949108231", "https://openalex.org/W2950210960", "https://openalex.org/W2951562155", "https://openalex.org/W2962735828", "https://openalex.org/W3029645440", "https://openalex.org/W3100265218", "https://openalex.org/W3104119384"], "related_works": ["https://openalex.org/W2147880316", "https://openalex.org/W2125838338", "https://openalex.org/W2156515921", "https://openalex.org/W2158188757", "https://openalex.org/W1934019294", "https://openalex.org/W1766290689", "https://openalex.org/W2008652694", "https://openalex.org/W2141099517", "https://openalex.org/W2105644991", "https://openalex.org/W2064675550", "https://openalex.org/W2159080219", "https://openalex.org/W2137813581", "https://openalex.org/W1560512119", "https://openalex.org/W2296283641", "https://openalex.org/W1940872118", "https://openalex.org/W2158899491", "https://openalex.org/W2109189215", "https://openalex.org/W2034797903", "https://openalex.org/W1773803948", "https://openalex.org/W1511986666"], "abstract_inverted_index": {"In": [0, 121], "sequence": [1], "modeling,": [2], "we": [3, 80, 99, 127, 140, 157], "often": [4], "wish": [5], "to": [6, 123], "represent": [7], "complex": [8], "interaction": [9], "between": [10], "labels,": [11], "such": [12, 78], "as": [13, 60, 167], "when": [14, 25, 139, 156, 193], "performing": [15], "multiple,": [16], "cascaded": [17, 153, 176, 210], "labeling": [18], "tasks": [19], "on": [20, 178], "the": [21, 118, 150, 197, 220], "same": [22], "sequence,": [23], "or": [24], "long-range": [26], "dependencies": [27], "exist.": [28], "We": [29, 171], "present": [30, 128], "dynamic": [31, 62], "conditional": [32, 40, 125], "random": [33, 41], "fields": [34, 42], "(DCRFs),": [35], "a": [36, 50, 95, 102, 107, 147, 159, 205, 209, 215], "generalization": [37], "of": [38, 52, 109, 149], "linear-chain": [39, 110, 216], "(CRFs)": [43], "in": [44, 61, 77, 144, 168, 208], "which": [45], "each": [46, 164], "time": [47], "slice": [48], "contains": [49], "set": [51, 162], "state": [53, 58, 165], "variables": [54], "and": [55, 152, 175, 182, 200], "edges\u2014a": [56], "distributed": [57], "representation": [59], "Bayesian": [63], "networks": [64], "(DBNs)\u2014and": [65], "parameters": [66], "are": [67, 141], "tied": [68], "across": [69], "slices.": [70], "Since": [71], "exact": [72], "inference": [73, 83], "can": [74, 190], "be": [75], "intractable": [76], "models,": [79], "perform": [81], "approximate": [82], "using": [84, 115], "several": [85], "schedules": [86], "for": [87, 132, 138, 155, 163, 202], "belief": [88], "propagation,": [89], "including": [90], "tree-based": [91], "reparameterization": [92], "(TRP).": [93], "On": [94], "natural-language": [96], "chunking": [97], "task,": [98], "show": [100], "that": [101, 187, 201, 218], "DCRF": [103, 206], "performs": [104, 212], "better": [105, 213], "than": [106, 214], "series": [108], "CRFs,": [111], "achieving": [112], "comparable": [113], "performance": [114], "only": [116, 146], "half": [117], "training": [119, 133, 174, 177, 189], "data.": [120], "addition": [122], "maximum": [124], "likelihood,": [126], "two": [129], "alternative": [130], "approaches": [131], "DCRFs:": [134], "marginal": [135, 173, 188], "likelihood": [136], "training,": [137, 154], "primarily": [142], "interested": [143], "predicting": [145], "subset": [148], "variables,": [151, 199], "have": [158], "distinct": [160], "data": [161, 181], "variable,": [166], "transfer": [169, 203], "learning.": [170], "evaluate": [172], "both": [179], "synthetic": [180], "real-world": [183], "text": [184], "data,": [185], "finding": [186], "improve": [191], "accuracy": [192], "uncertainty": [194], "exists": [195], "over": [196], "latent": [198], "learning,": [204], "trained": [207], "fashion": [211], "CRF": [217], "predicts": [219], "final": [221], "task": [222], "directly.": [223]}, "counts_by_year": [{"year": 2025, "cited_by_count": 1}, {"year": 2024, "cited_by_count": 3}, {"year": 2023, "cited_by_count": 6}, {"year": 2022, "cited_by_count": 7}, {"year": 2021, "cited_by_count": 19}, {"year": 2020, "cited_by_count": 17}, {"year": 2019, "cited_by_count": 13}, {"year": 2018, "cited_by_count": 12}, {"year": 2017, "cited_by_count": 15}, {"year": 2016, "cited_by_count": 14}, {"year": 2015, "cited_by_count": 16}, {"year": 2014, "cited_by_count": 25}, {"year": 2013, "cited_by_count": 19}, {"year": 2012, "cited_by_count": 17}], "updated_date": "2026-08-04T08:18:43.703281", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W2156515921", "doi": "https://doi.org/10.3115/1073445.1073473", "title": "Shallow parsing with conditional random fields", "display_name": "Shallow parsing with conditional random fields", "relevance_score": 1073.966, "publication_year": 2003, "publication_date": "2003-01-01", "ids": {"openalex": "https://openalex.org/W2156515921", "doi": "https://doi.org/10.3115/1073445.1073473", "mag": "2156515921"}, "language": "en", "primary_location": {"id": "doi:10.3115/1073445.1073473", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1073445.1073473", "pdf_url": "http://dl.acm.org/ft_gateway.cfm?id=1073473&type=pdf", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - NAACL '03", "raw_type": "proceedings-article"}, "type": "conference-paper", "indexed_in": ["crossref"], "open_access": {"is_oa": true, "oa_status": "gold", "oa_url": "http://dl.acm.org/ft_gateway.cfm?id=1073473&type=pdf", "any_repository_has_fulltext": null}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5101544732", "display_name": "Fei Sha", "orcid": "https://orcid.org/0000-0002-9382-0010"}, "institutions": [{"id": "https://openalex.org/I79576946", "display_name": "University of Pennsylvania", "ror": "https://ror.org/00b30xv10", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I79576946"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Fei Sha", "raw_affiliation_strings": ["University of Pennsylvania, Philadelphia, PA"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Pennsylvania, Philadelphia, PA", "institution_ids": ["https://openalex.org/I79576946"]}]}, {"author_position": "last", "author": {"id": "https://openalex.org/A5044708805", "display_name": "Fernando Pereira", "orcid": "https://orcid.org/0000-0001-6100-947X"}, "institutions": [{"id": "https://openalex.org/I79576946", "display_name": "University of Pennsylvania", "ror": "https://ror.org/00b30xv10", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I79576946"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Fernando Pereira", "raw_affiliation_strings": ["University of Pennsylvania, Philadelphia, PA"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Pennsylvania, Philadelphia, PA", "institution_ids": ["https://openalex.org/I79576946"]}]}], "institutions": [], "countries_distinct_count": 1, "institutions_distinct_count": 1, "corresponding_author_ids": [], "corresponding_institution_ids": ["https://openalex.org/I79576946"], "apc_list": null, "apc_paid": null, "fwci": 51.0757, "has_fulltext": true, "cited_by_count": 1251, "citation_normalized_percentile": {"value": 0.99970213, "is_in_top_1_percent": true, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 94, "max": 100}, "biblio": {"volume": "1", "issue": null, "first_page": "134", "last_page": "141"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 1.0, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 1.0, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9998999834060669, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10201", "display_name": "Speech Recognition and Synthesis", "score": 0.9973999857902527, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/conditional-random-field", "display_name": "Conditional random field", "score": 0.9632378816604614}, {"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.8415220379829407}, {"id": "https://openalex.org/keywords/chunking", "display_name": "Chunking (psychology)", "score": 0.7710052132606506}, {"id": "https://openalex.org/keywords/parsing", "display_name": "Parsing", "score": 0.7390148043632507}, {"id": "https://openalex.org/keywords/sequence-labeling", "display_name": "Sequence labeling", "score": 0.6991968750953674}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.6813458800315857}, {"id": "https://openalex.org/keywords/crfs", "display_name": "CRFS", "score": 0.5946848392486572}, {"id": "https://openalex.org/keywords/generative-grammar", "display_name": "Generative grammar", "score": 0.5754933953285217}, {"id": "https://openalex.org/keywords/natural-language-processing", "display_name": "Natural language processing", "score": 0.5733460187911987}, {"id": "https://openalex.org/keywords/conditional-entropy", "display_name": "Conditional entropy", "score": 0.5475512742996216}, {"id": "https://openalex.org/keywords/sequence", "display_name": "Sequence (biology)", "score": 0.4810331463813782}, {"id": "https://openalex.org/keywords/task", "display_name": "Task (project management)", "score": 0.4443749785423279}, {"id": "https://openalex.org/keywords/principle-of-maximum-entropy", "display_name": "Principle of maximum entropy", "score": 0.3970979154109955}, {"id": "https://openalex.org/keywords/machine-learning", "display_name": "Machine learning", "score": 0.3492504954338074}], "concepts": [{"id": "https://openalex.org/C152565575", "wikidata": "https://www.wikidata.org/wiki/Q1124538", "display_name": "Conditional random field", "level": 2, "score": 0.9632378816604614}, {"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.8415220379829407}, {"id": "https://openalex.org/C203357204", "wikidata": "https://www.wikidata.org/wiki/Q1089605", "display_name": "Chunking (psychology)", "level": 2, "score": 0.7710052132606506}, {"id": "https://openalex.org/C186644900", "wikidata": "https://www.wikidata.org/wiki/Q194152", "display_name": "Parsing", "level": 2, "score": 0.7390148043632507}, {"id": "https://openalex.org/C35639132", "wikidata": "https://www.wikidata.org/wiki/Q7452468", "display_name": "Sequence labeling", "level": 3, "score": 0.6991968750953674}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.6813458800315857}, {"id": "https://openalex.org/C2775953691", "wikidata": "https://www.wikidata.org/wiki/Q5013874", "display_name": "CRFS", "level": 3, "score": 0.5946848392486572}, {"id": "https://openalex.org/C39890363", "wikidata": "https://www.wikidata.org/wiki/Q36108", "display_name": "Generative grammar", "level": 2, "score": 0.5754933953285217}, {"id": "https://openalex.org/C204321447", "wikidata": "https://www.wikidata.org/wiki/Q30642", "display_name": "Natural language processing", "level": 1, "score": 0.5733460187911987}, {"id": "https://openalex.org/C101721835", "wikidata": "https://www.wikidata.org/wiki/Q813908", "display_name": "Conditional entropy", "level": 3, "score": 0.5475512742996216}, {"id": "https://openalex.org/C2778112365", "wikidata": "https://www.wikidata.org/wiki/Q3511065", "display_name": "Sequence (biology)", "level": 2, "score": 0.4810331463813782}, {"id": "https://openalex.org/C2780451532", "wikidata": "https://www.wikidata.org/wiki/Q759676", "display_name": "Task (project management)", "level": 2, "score": 0.4443749785423279}, {"id": "https://openalex.org/C9679016", "wikidata": "https://www.wikidata.org/wiki/Q1417473", "display_name": "Principle of maximum entropy", "level": 2, "score": 0.3970979154109955}, {"id": "https://openalex.org/C119857082", "wikidata": "https://www.wikidata.org/wiki/Q2539", "display_name": "Machine learning", "level": 1, "score": 0.3492504954338074}, {"id": "https://openalex.org/C187736073", "wikidata": "https://www.wikidata.org/wiki/Q2920921", "display_name": "Management", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C86803240", "wikidata": "https://www.wikidata.org/wiki/Q420", "display_name": "Biology", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C54355233", "wikidata": "https://www.wikidata.org/wiki/Q7162", "display_name": "Genetics", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C162324750", "wikidata": "https://www.wikidata.org/wiki/Q8134", "display_name": "Economics", "level": 0, "score": 0.0}], "mesh": [], "locations_count": 4, "locations": [{"id": "doi:10.3115/1073445.1073473", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1073445.1073473", "pdf_url": "http://dl.acm.org/ft_gateway.cfm?id=1073473&type=pdf", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - NAACL '03", "raw_type": "proceedings-article"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.10.9849", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.10.9849", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://acl.ldc.upenn.edu/N/N03/N03-1028.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.11.527", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.11.527", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cis.upenn.edu/~feisha/pubs/shallow03.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.81.5323", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.81.5323", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cis.upenn.edu/~pereira/papers/shallow.pdf", "raw_type": "text"}], "best_oa_location": {"id": "doi:10.3115/1073445.1073473", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1073445.1073473", "pdf_url": "http://dl.acm.org/ft_gateway.cfm?id=1073473&type=pdf", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - NAACL '03", "raw_type": "proceedings-article"}, "sustainable_development_goals": [{"display_name": "Quality Education", "score": 0.8100000023841858, "id": "https://metadata.un.org/sdg/4"}], "awards": [], "funders": [], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2156515921.pdf", "grobid_xml": "https://content.openalex.org/works/W2156515921.grobid-xml"}, "referenced_works_count": 43, "referenced_works": ["https://openalex.org/W793766733", "https://openalex.org/W1520377376", "https://openalex.org/W1529196404", "https://openalex.org/W1553458173", "https://openalex.org/W1592796124", "https://openalex.org/W1623072288", "https://openalex.org/W1773803948", "https://openalex.org/W1810157568", "https://openalex.org/W1823542770", "https://openalex.org/W1932968309", "https://openalex.org/W1934019294", "https://openalex.org/W1988995507", "https://openalex.org/W1995945562", "https://openalex.org/W2001792610", "https://openalex.org/W2008652694", "https://openalex.org/W2057399676", "https://openalex.org/W2096175520", "https://openalex.org/W2097125878", "https://openalex.org/W2098841537", "https://openalex.org/W2098921539", "https://openalex.org/W2099942883", "https://openalex.org/W2100796029", "https://openalex.org/W2102667697", "https://openalex.org/W2104118994", "https://openalex.org/W2114521167", "https://openalex.org/W2117400858", "https://openalex.org/W2131297983", "https://openalex.org/W2137213923", "https://openalex.org/W2143458716", "https://openalex.org/W2145948275", "https://openalex.org/W2147880316", "https://openalex.org/W2160842254", "https://openalex.org/W2161290181", "https://openalex.org/W2797062063", "https://openalex.org/W2949995692", "https://openalex.org/W2951299559", "https://openalex.org/W2951562155", "https://openalex.org/W2962735828", "https://openalex.org/W2963847008", "https://openalex.org/W2994982620", "https://openalex.org/W4293775970", "https://openalex.org/W6631934416", "https://openalex.org/W6675187287"], "related_works": ["https://openalex.org/W2962906565", "https://openalex.org/W2798423868", "https://openalex.org/W3015678144", "https://openalex.org/W2011251309", "https://openalex.org/W2076440176", "https://openalex.org/W2055466819", "https://openalex.org/W2140585957", "https://openalex.org/W2898922131", "https://openalex.org/W2150969560", "https://openalex.org/W2385117199"], "abstract_inverted_index": {"Conditional": [0], "random": [1, 54], "fields": [2], "for": [3, 114], "sequence": [4, 19, 22], "labeling": [5, 23], "offer": [6], "advantages": [7], "over": [8], "both": [9], "generative": [10], "models": [11, 98], "like": [12], "HMMs": [13], "and": [14, 41, 72, 99, 104, 111], "classifiers": [15], "applied": [16], "at": [17], "each": [18], "position.": [20], "Among": [21], "tasks": [24], "in": [25, 89], "language": [26], "processing,": [27], "shallow": [28, 109], "parsing": [29, 110], "has": [30], "received": [31], "much": [32], "attention,": [33], "with": [34], "the": [35, 69], "development": [36], "of": [37], "standard": [38], "evaluation": [39], "datasets": [40], "extensive": [42, 95], "comparison": [43], "among": [44], "methods.": [45], "We": [46, 93], "show": [47], "here": [48], "how": [49], "to": [50, 56], "train": [51], "a": [52], "conditional": [53], "field": [55], "achieve": [57], "performance": [58], "as": [59, 61], "good": [60], "any": [62, 75], "reported": [63, 76], "base": [64], "noun-phrase": [65], "chunking": [66], "method": [67], "on": [68, 83, 108], "CoNLL": [70], "task,": [71], "better": [73], "than": [74], "single": [77], "model.": [78], "Improved": [79], "training": [80, 100, 112], "methods": [81, 101, 113], "based": [82], "modern": [84], "optimization": [85], "algorithms": [86], "were": [87], "critical": [88], "achieving": [90], "these": [91], "results.": [92], "present": [94], "comparisons": [96], "between": [97], "that": [102], "confirm": [103], "strengthen": [105], "previous": [106], "results": [107], "maximum-entropy": [115], "models.": [116]}, "counts_by_year": [{"year": 2026, "cited_by_count": 1}, {"year": 2025, "cited_by_count": 4}, {"year": 2024, "cited_by_count": 7}, {"year": 2023, "cited_by_count": 9}, {"year": 2022, "cited_by_count": 10}, {"year": 2021, "cited_by_count": 21}, {"year": 2020, "cited_by_count": 23}, {"year": 2019, "cited_by_count": 26}, {"year": 2018, "cited_by_count": 44}, {"year": 2017, "cited_by_count": 44}, {"year": 2016, "cited_by_count": 55}, {"year": 2015, "cited_by_count": 52}, {"year": 2014, "cited_by_count": 84}, {"year": 2013, "cited_by_count": 88}, {"year": 2012, "cited_by_count": 93}], "updated_date": "2026-07-29T14:22:42.915294", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W2112796928", "doi": "https://doi.org/10.1109/5.726791", "title": "Gradient-based learning applied to document recognition", "display_name": "Gradient-based learning applied to document recognition", "relevance_score": 996.2877, "publication_year": 1998, "publication_date": "1998-01-01", "ids": {"openalex": "https://openalex.org/W2112796928", "doi": "https://doi.org/10.1109/5.726791", "mag": "2112796928"}, "language": "en", "primary_location": {"id": "doi:10.1109/5.726791", "is_oa": false, "landing_page_url": "https://doi.org/10.1109/5.726791", "pdf_url": null, "source": {"id": "https://openalex.org/S68686220", "display_name": "Proceedings of the IEEE", "issn_l": "0018-9219", "issn": ["0018-9219", "1558-2256"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310319808", "host_organization_name": "Institute of Electrical and Electronics Engineers", "host_organization_lineage": ["https://openalex.org/P4310319808"], "host_organization_lineage_names": ["Institute of Electrical and Electronics Engineers"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the IEEE", "raw_type": "journal-article"}, "type": "article", "indexed_in": ["crossref"], "open_access": {"is_oa": true, "oa_status": "green", "oa_url": "https://hal.science/hal-03926082/document", "any_repository_has_fulltext": true}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5001226970", "display_name": "Yann LeCun", "orcid": null}, "institutions": [{"id": "https://openalex.org/I1283103587", "display_name": "AT&T (United States)", "ror": "https://ror.org/02bbd5539", "country_code": "US", "type": "company", "lineage": ["https://openalex.org/I1283103587"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Y. Lecun", "raw_affiliation_strings": ["Speech and Image Processing Services Research Laboratory, AT and T Research Laboratories, Red Bank, NJ, USA", "Speech and Image Processing Services Research Laboratory"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Speech and Image Processing Services Research Laboratory, AT and T Research Laboratories, Red Bank, NJ, USA", "institution_ids": ["https://openalex.org/I1283103587"]}, {"raw_affiliation_string": "Speech and Image Processing Services Research Laboratory", "institution_ids": []}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5019206666", "display_name": "L\u00e9on Bottou", "orcid": "https://orcid.org/0000-0002-9894-8128"}, "institutions": [{"id": "https://openalex.org/I1283103587", "display_name": "AT&T (United States)", "ror": "https://ror.org/02bbd5539", "country_code": "US", "type": "company", "lineage": ["https://openalex.org/I1283103587"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "L. Bottou", "raw_affiliation_strings": ["Speech and Image Processing Services Research Laboratory, AT and T Research Laboratories, Red Bank, NJ, USA", "Speech and Image Processing Services Research Laboratory"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Speech and Image Processing Services Research Laboratory, AT and T Research Laboratories, Red Bank, NJ, USA", "institution_ids": ["https://openalex.org/I1283103587"]}, {"raw_affiliation_string": "Speech and Image Processing Services Research Laboratory", "institution_ids": []}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5086198262", "display_name": "Yoshua Bengio", "orcid": "https://orcid.org/0000-0002-9322-3515"}, "institutions": [{"id": "https://openalex.org/I70931966", "display_name": "Universit\u00e9 de Montr\u00e9al", "ror": "https://ror.org/0161xgx34", "country_code": "CA", "type": "education", "lineage": ["https://openalex.org/I70931966"]}], "countries": ["CA"], "is_corresponding": false, "raw_author_name": "Y. Bengio", "raw_affiliation_strings": ["D\u00e9partement D'Informatique et de Recherche Op\u00e9rationelle, Universit\u00e9 de Montreal, Montreal, QUE, Canada", "Speech and Image Processing Services Research Laboratory", "Universit\u00e9 de Montr\u00e9al"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "D\u00e9partement D'Informatique et de Recherche Op\u00e9rationelle, Universit\u00e9 de Montreal, Montreal, QUE, Canada", "institution_ids": ["https://openalex.org/I70931966"]}, {"raw_affiliation_string": "Speech and Image Processing Services Research Laboratory", "institution_ids": []}, {"raw_affiliation_string": "Universit\u00e9 de Montr\u00e9al", "institution_ids": ["https://openalex.org/I70931966"]}]}, {"author_position": "last", "author": {"id": "https://openalex.org/A5026605560", "display_name": "Patrick Haffner", "orcid": "https://orcid.org/0000-0002-2319-5109"}, "institutions": [{"id": "https://openalex.org/I1283103587", "display_name": "AT&T (United States)", "ror": "https://ror.org/02bbd5539", "country_code": "US", "type": "company", "lineage": ["https://openalex.org/I1283103587"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "P. Haffner", "raw_affiliation_strings": ["Speech and Image Processing Services Research Laboratory, AT and T Research Laboratories, Red Bank, NJ, USA", "Speech and Image Processing Services Research Laboratory"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Speech and Image Processing Services Research Laboratory, AT and T Research Laboratories, Red Bank, NJ, USA", "institution_ids": ["https://openalex.org/I1283103587"]}, {"raw_affiliation_string": "Speech and Image Processing Services Research Laboratory", "institution_ids": []}]}], "institutions": [], "countries_distinct_count": 2, "institutions_distinct_count": 2, "corresponding_author_ids": [], "corresponding_institution_ids": [], "apc_list": null, "apc_paid": null, "fwci": 11.0628, "has_fulltext": true, "cited_by_count": 58873, "citation_normalized_percentile": {"value": 0.98679527, "is_in_top_1_percent": false, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 99, "max": 100}, "biblio": {"volume": "86", "issue": "11", "first_page": "2278", "last_page": "2324"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10601", "display_name": "Handwritten Text Recognition Techniques", "score": 0.9995999932289124, "subfield": {"id": "https://openalex.org/subfields/1707", "display_name": "Computer Vision and Pattern Recognition"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10601", "display_name": "Handwritten Text Recognition Techniques", "score": 0.9995999932289124, "subfield": {"id": "https://openalex.org/subfields/1707", "display_name": "Computer Vision and Pattern Recognition"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T14339", "display_name": "Image Processing and 3D Reconstruction", "score": 0.9968000054359436, "subfield": {"id": "https://openalex.org/subfields/1707", "display_name": "Computer Vision and Pattern Recognition"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10320", "display_name": "Neural Networks and Applications", "score": 0.9950000047683716, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.8254276514053345}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.6142195463180542}, {"id": "https://openalex.org/keywords/convolutional-neural-network", "display_name": "Convolutional neural network", "score": 0.5978816747665405}, {"id": "https://openalex.org/keywords/intelligent-character-recognition", "display_name": "Intelligent character recognition", "score": 0.5887831449508667}, {"id": "https://openalex.org/keywords/handwriting-recognition", "display_name": "Handwriting recognition", "score": 0.5319666266441345}, {"id": "https://openalex.org/keywords/transformer", "display_name": "Transformer", "score": 0.5122293829917908}, {"id": "https://openalex.org/keywords/artificial-neural-network", "display_name": "Artificial neural network", "score": 0.49849534034729004}, {"id": "https://openalex.org/keywords/pattern-recognition", "display_name": "Pattern recognition (psychology)", "score": 0.49462172389030457}, {"id": "https://openalex.org/keywords/handwriting", "display_name": "Handwriting", "score": 0.46896353363990784}, {"id": "https://openalex.org/keywords/preprocessor", "display_name": "Preprocessor", "score": 0.4614042639732361}, {"id": "https://openalex.org/keywords/deep-learning", "display_name": "Deep learning", "score": 0.460247665643692}, {"id": "https://openalex.org/keywords/graph", "display_name": "Graph", "score": 0.4320318102836609}, {"id": "https://openalex.org/keywords/speech-recognition", "display_name": "Speech recognition", "score": 0.35688453912734985}, {"id": "https://openalex.org/keywords/machine-learning", "display_name": "Machine learning", "score": 0.34401291608810425}, {"id": "https://openalex.org/keywords/feature-extraction", "display_name": "Feature extraction", "score": 0.29552727937698364}, {"id": "https://openalex.org/keywords/character-recognition", "display_name": "Character recognition", "score": 0.19865167140960693}, {"id": "https://openalex.org/keywords/theoretical-computer-science", "display_name": "Theoretical computer science", "score": 0.08571499586105347}], "concepts": [{"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.8254276514053345}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.6142195463180542}, {"id": "https://openalex.org/C81363708", "wikidata": "https://www.wikidata.org/wiki/Q17084460", "display_name": "Convolutional neural network", "level": 2, "score": 0.5978816747665405}, {"id": "https://openalex.org/C44868376", "wikidata": "https://www.wikidata.org/wiki/Q3099089", "display_name": "Intelligent character recognition", "level": 4, "score": 0.5887831449508667}, {"id": "https://openalex.org/C112640561", "wikidata": "https://www.wikidata.org/wiki/Q2440634", "display_name": "Handwriting recognition", "level": 3, "score": 0.5319666266441345}, {"id": "https://openalex.org/C66322947", "wikidata": "https://www.wikidata.org/wiki/Q11658", "display_name": "Transformer", "level": 3, "score": 0.5122293829917908}, {"id": "https://openalex.org/C50644808", "wikidata": "https://www.wikidata.org/wiki/Q192776", "display_name": "Artificial neural network", "level": 2, "score": 0.49849534034729004}, {"id": "https://openalex.org/C153180895", "wikidata": "https://www.wikidata.org/wiki/Q7148389", "display_name": "Pattern recognition (psychology)", "level": 2, "score": 0.49462172389030457}, {"id": "https://openalex.org/C2779386606", "wikidata": "https://www.wikidata.org/wiki/Q2393642", "display_name": "Handwriting", "level": 2, "score": 0.46896353363990784}, {"id": "https://openalex.org/C34736171", "wikidata": "https://www.wikidata.org/wiki/Q918333", "display_name": "Preprocessor", "level": 2, "score": 0.4614042639732361}, {"id": "https://openalex.org/C108583219", "wikidata": "https://www.wikidata.org/wiki/Q197536", "display_name": "Deep learning", "level": 2, "score": 0.460247665643692}, {"id": "https://openalex.org/C132525143", "wikidata": "https://www.wikidata.org/wiki/Q141488", "display_name": "Graph", "level": 2, "score": 0.4320318102836609}, {"id": "https://openalex.org/C28490314", "wikidata": "https://www.wikidata.org/wiki/Q189436", "display_name": "Speech recognition", "level": 1, "score": 0.35688453912734985}, {"id": "https://openalex.org/C119857082", "wikidata": "https://www.wikidata.org/wiki/Q2539", "display_name": "Machine learning", "level": 1, "score": 0.34401291608810425}, {"id": "https://openalex.org/C52622490", "wikidata": "https://www.wikidata.org/wiki/Q1026626", "display_name": "Feature extraction", "level": 2, "score": 0.29552727937698364}, {"id": "https://openalex.org/C2987247673", "wikidata": "https://www.wikidata.org/wiki/Q167555", "display_name": "Character recognition", "level": 3, "score": 0.19865167140960693}, {"id": "https://openalex.org/C80444323", "wikidata": "https://www.wikidata.org/wiki/Q2878974", "display_name": "Theoretical computer science", "level": 1, "score": 0.08571499586105347}, {"id": "https://openalex.org/C121332964", "wikidata": "https://www.wikidata.org/wiki/Q413", "display_name": "Physics", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C165801399", "wikidata": "https://www.wikidata.org/wiki/Q25428", "display_name": "Voltage", "level": 2, "score": 0.0}, {"id": "https://openalex.org/C62520636", "wikidata": "https://www.wikidata.org/wiki/Q944", "display_name": "Quantum mechanics", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C115961682", "wikidata": "https://www.wikidata.org/wiki/Q860623", "display_name": "Image (mathematics)", "level": 2, "score": 0.0}], "mesh": [], "locations_count": 2, "locations": [{"id": "doi:10.1109/5.726791", "is_oa": false, "landing_page_url": "https://doi.org/10.1109/5.726791", "pdf_url": null, "source": {"id": "https://openalex.org/S68686220", "display_name": "Proceedings of the IEEE", "issn_l": "0018-9219", "issn": ["0018-9219", "1558-2256"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310319808", "host_organization_name": "Institute of Electrical and Electronics Engineers", "host_organization_lineage": ["https://openalex.org/P4310319808"], "host_organization_lineage_names": ["Institute of Electrical and Electronics Engineers"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the IEEE", "raw_type": "journal-article"}, {"id": "pmh:oai:HAL:hal-03926082v1", "is_oa": true, "landing_page_url": "https://hal.science/hal-03926082", "pdf_url": "https://hal.science/hal-03926082/document", "source": {"id": "https://openalex.org/S4306402512", "display_name": "HAL (Le Centre pour la Communication Scientifique Directe)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I1294671590", "host_organization_name": "Centre National de la Recherche Scientifique", "host_organization_lineage": ["https://openalex.org/I1294671590"], "host_organization_lineage_names": [], "type": "repository"}, "license": "other-oa", "license_id": "https://openalex.org/licenses/other-oa", "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Proceedings of the IEEE, 1998, 86 (11), pp.2278-2324. &#x27E8;10.1109/5.726791&#x27E9;", "raw_type": "info:eu-repo/semantics/article"}], "best_oa_location": {"id": "pmh:oai:HAL:hal-03926082v1", "is_oa": true, "landing_page_url": "https://hal.science/hal-03926082", "pdf_url": "https://hal.science/hal-03926082/document", "source": {"id": "https://openalex.org/S4306402512", "display_name": "HAL (Le Centre pour la Communication Scientifique Directe)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I1294671590", "host_organization_name": "Centre National de la Recherche Scientifique", "host_organization_lineage": ["https://openalex.org/I1294671590"], "host_organization_lineage_names": [], "type": "repository"}, "license": "other-oa", "license_id": "https://openalex.org/licenses/other-oa", "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Proceedings of the IEEE, 1998, 86 (11), pp.2278-2324. &#x27E8;10.1109/5.726791&#x27E9;", "raw_type": "info:eu-repo/semantics/article"}, "sustainable_development_goals": [], "awards": [], "funders": [], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2112796928.pdf", "grobid_xml": "https://content.openalex.org/works/W2112796928.grobid-xml"}, "referenced_works_count": 135, "referenced_works": ["https://openalex.org/W19621276", "https://openalex.org/W28586472", "https://openalex.org/W66978610", "https://openalex.org/W85412639", "https://openalex.org/W98859974", "https://openalex.org/W103129759", "https://openalex.org/W146900863", "https://openalex.org/W169539560", "https://openalex.org/W183625566", "https://openalex.org/W324611197", "https://openalex.org/W413857758", "https://openalex.org/W811578723", "https://openalex.org/W1530666108", "https://openalex.org/W1544211475", "https://openalex.org/W1547224907", "https://openalex.org/W1553004968", "https://openalex.org/W1575881144", "https://openalex.org/W1597009674", "https://openalex.org/W1625762979", "https://openalex.org/W1654022110", "https://openalex.org/W1667072054", "https://openalex.org/W1676820704", "https://openalex.org/W1761621746", "https://openalex.org/W1836880760", "https://openalex.org/W1877570817", "https://openalex.org/W1919233617", "https://openalex.org/W1975113431", "https://openalex.org/W1991133427", "https://openalex.org/W1992774725", "https://openalex.org/W1994065256", "https://openalex.org/W1994530392", "https://openalex.org/W1998255116", "https://openalex.org/W1999497791", "https://openalex.org/W2006544565", "https://openalex.org/W2007857129", "https://openalex.org/W2010315761", "https://openalex.org/W2010581677", "https://openalex.org/W2030781528", "https://openalex.org/W2035526030", "https://openalex.org/W2041460909", "https://openalex.org/W2042492924", "https://openalex.org/W2046485094", "https://openalex.org/W2047121664", "https://openalex.org/W2053176763", "https://openalex.org/W2055075080", "https://openalex.org/W2056695679", "https://openalex.org/W2056763477", "https://openalex.org/W2057200159", "https://openalex.org/W2057619148", "https://openalex.org/W2060604179", "https://openalex.org/W2063541597", "https://openalex.org/W2087347434", "https://openalex.org/W2090614046", "https://openalex.org/W2091987367", "https://openalex.org/W2093717447", "https://openalex.org/W2095757522", "https://openalex.org/W2095891604", "https://openalex.org/W2097316030", "https://openalex.org/W2099070536", "https://openalex.org/W2100921332", "https://openalex.org/W2103496339", "https://openalex.org/W2104867159", "https://openalex.org/W2107878631", "https://openalex.org/W2112957975", "https://openalex.org/W2113292028", "https://openalex.org/W2115240329", "https://openalex.org/W2116360511", "https://openalex.org/W2117671523", "https://openalex.org/W2119113516", "https://openalex.org/W2124351082", "https://openalex.org/W2125529971", "https://openalex.org/W2125838338", "https://openalex.org/W2126514931", "https://openalex.org/W2128652941", "https://openalex.org/W2131877510", "https://openalex.org/W2132131403", "https://openalex.org/W2132793646", "https://openalex.org/W2132904398", "https://openalex.org/W2134267682", "https://openalex.org/W2134429390", "https://openalex.org/W2135936685", "https://openalex.org/W2137291015", "https://openalex.org/W2137440383", "https://openalex.org/W2140005396", "https://openalex.org/W2140539590", "https://openalex.org/W2141207507", "https://openalex.org/W2144354855", "https://openalex.org/W2144405074", "https://openalex.org/W2147800946", "https://openalex.org/W2148099973", "https://openalex.org/W2148295954", "https://openalex.org/W2148603752", "https://openalex.org/W2149814369", "https://openalex.org/W2151871503", "https://openalex.org/W2154579312", "https://openalex.org/W2156909104", "https://openalex.org/W2158670134", "https://openalex.org/W2161523118", "https://openalex.org/W2162794177", "https://openalex.org/W2165668746", "https://openalex.org/W2165959773", "https://openalex.org/W2166559794", "https://openalex.org/W2168263526", "https://openalex.org/W2170599822", "https://openalex.org/W2170837066", "https://openalex.org/W2171590421", "https://openalex.org/W2346626577", "https://openalex.org/W2432517183", "https://openalex.org/W2565808444", "https://openalex.org/W2566703758", "https://openalex.org/W2598912124", "https://openalex.org/W2606748186", "https://openalex.org/W2609716011", "https://openalex.org/W2728988083", "https://openalex.org/W2766736793", "https://openalex.org/W2798500587", "https://openalex.org/W3004732066", "https://openalex.org/W3016210511", "https://openalex.org/W3017143921", "https://openalex.org/W3022861191", "https://openalex.org/W3101571078", "https://openalex.org/W3139633029", "https://openalex.org/W3207021134", "https://openalex.org/W4206670532", "https://openalex.org/W4212774754", "https://openalex.org/W4301028212", "https://openalex.org/W6601183909", "https://openalex.org/W6602736415", "https://openalex.org/W6603414532", "https://openalex.org/W6604275113", "https://openalex.org/W6635935089", "https://openalex.org/W6637187546", "https://openalex.org/W6678720029", "https://openalex.org/W6682751323", "https://openalex.org/W6776675433"], "related_works": ["https://openalex.org/W4386428871", "https://openalex.org/W3199359807", "https://openalex.org/W4220954837", "https://openalex.org/W3047607512", "https://openalex.org/W3003949997", "https://openalex.org/W4390983538", "https://openalex.org/W2110485610", "https://openalex.org/W183832189", "https://openalex.org/W3163065387", "https://openalex.org/W2406729210"], "abstract_inverted_index": {"Multilayer": [0], "neural": [1, 69, 172], "networks": [2, 114], "trained": [3, 122], "with": [4, 45, 77, 177], "the": [5, 9, 78, 145, 151], "back-propagation": [6], "algorithm": [7], "constitute": [8], "best": [10], "example": [11], "of": [12, 80, 96, 147, 153], "a": [13, 32, 62, 163], "successful": [14], "gradient": [15], "based": [16], "learning": [17, 25, 109], "technique.": [18], "Given": [19], "an": [20, 131], "appropriate": [21], "network": [22, 160, 173], "architecture,": [23], "gradient-based": [24, 125], "algorithms": [26], "can": [27, 37], "be": [28, 121], "used": [29], "to": [30, 54, 75, 85, 120, 129, 181], "synthesize": [31], "complex": [33], "decision": [34], "surface": [35], "that": [36], "classify": [38], "high-dimensional": [39], "patterns,": [40], "such": [41, 117], "as": [42, 128], "handwritten": [43, 55, 64], "characters,": [44], "minimal": [46], "preprocessing.": [47], "This": [48], "paper": [49], "reviews": [50], "various": [51], "methods": [52, 126], "applied": [53], "character": [56, 174], "recognition": [57, 66, 92, 140], "and": [58, 104, 150, 187, 194], "compares": [59], "them": [60], "on": [61, 185], "standard": [63], "digit": [65], "task.": [67], "Convolutional": [68], "networks,": [70], "which": [71], "are": [72, 83, 94, 141], "specifically": [73], "designed": [74], "deal": [76], "variability": [79], "2D": [81], "shapes,": [82], "shown": [84], "outperform": [86], "all": [87], "other": [88], "techniques.": [89], "Real-life": [90], "document": [91], "systems": [93, 119, 136], "composed": [95], "multiple": [97], "modules": [98], "including": [99], "field": [100], "extraction,": [101], "segmentation": [102], "recognition,": [103], "language": [105], "modeling.": [106], "A": [107, 157], "new": [108], "paradigm,": [110], "called": [111], "graph": [112, 154, 158], "transformer": [113, 155, 159], "(GTN),": [115], "allows": [116], "multimodule": [118], "globally": [123], "using": [124], "so": [127], "minimize": [130], "overall": [132], "performance": [133], "measure.": [134], "Two": [135], "for": [137, 161], "online": [138], "handwriting": [139], "described.": [142, 168], "Experiments": [143], "demonstrate": [144], "advantage": [146], "global": [148, 178], "training,": [149], "flexibility": [152], "networks.": [156], "reading": [162], "bank": [164], "cheque": [165], "is": [166, 191], "also": [167], "It": [169, 190], "uses": [170], "convolutional": [171], "recognizers": [175], "combined": [176], "training": [179], "techniques": [180], "provide": [182], "record": [183], "accuracy": [184], "business": [186], "personal": [188], "cheques.": [189], "deployed": [192], "commercially": [193], "reads": [195], "several": [196], "million": [197], "cheques": [198], "per": [199], "day.": [200]}, "counts_by_year": [{"year": 2026, "cited_by_count": 2579}, {"year": 2025, "cited_by_count": 5946}, {"year": 2024, "cited_by_count": 5847}, {"year": 2023, "cited_by_count": 6003}, {"year": 2022, "cited_by_count": 5763}, {"year": 2021, "cited_by_count": 7033}, {"year": 2020, "cited_by_count": 6684}, {"year": 2019, "cited_by_count": 5976}, {"year": 2018, "cited_by_count": 4364}, {"year": 2017, "cited_by_count": 2924}, {"year": 2016, "cited_by_count": 1943}, {"year": 2015, "cited_by_count": 1294}, {"year": 2014, "cited_by_count": 662}, {"year": 2013, "cited_by_count": 417}, {"year": 2012, "cited_by_count": 279}], "updated_date": "2026-08-06T08:24:18.245995", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W2158823144", "doi": "https://doi.org/10.1145/1015330.1015422", "title": "Dynamic conditional random fields", "display_name": "Dynamic conditional random fields", "relevance_score": 878.7173, "publication_year": 2004, "publication_date": "2004-01-01", "ids": {"openalex": "https://openalex.org/W2158823144", "doi": "https://doi.org/10.1145/1015330.1015422", "mag": "2158823144"}, "language": "en", "primary_location": {"id": "doi:10.1145/1015330.1015422", "is_oa": false, "landing_page_url": "https://doi.org/10.1145/1015330.1015422", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Twenty-first international conference on Machine learning - ICML '04", "raw_type": "proceedings-article"}, "type": "conference-abstract", "indexed_in": ["crossref"], "open_access": {"is_oa": true, "oa_status": "green", "oa_url": "https://www.pure.ed.ac.uk/ws/files/14899616/p308_sutton.pdf", "any_repository_has_fulltext": true}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5028501178", "display_name": "Charles Sutton", "orcid": "https://orcid.org/0000-0002-0041-3820"}, "institutions": [{"id": "https://openalex.org/I24603500", "display_name": "University of Massachusetts Amherst", "ror": "https://ror.org/0072zz521", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I24603500"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Charles Sutton", "raw_affiliation_strings": ["University of Massachusetts, Amherst, MA"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Massachusetts, Amherst, MA", "institution_ids": ["https://openalex.org/I24603500"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5037673735", "display_name": "Khashayar Rohanimanesh", "orcid": null}, "institutions": [{"id": "https://openalex.org/I24603500", "display_name": "University of Massachusetts Amherst", "ror": "https://ror.org/0072zz521", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I24603500"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Khashayar Rohanimanesh", "raw_affiliation_strings": ["University of Massachusetts, Amherst, MA"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Massachusetts, Amherst, MA", "institution_ids": ["https://openalex.org/I24603500"]}]}, {"author_position": "last", "author": {"id": "https://openalex.org/A5107835063", "display_name": "Andrew McCallum", "orcid": null}, "institutions": [{"id": "https://openalex.org/I24603500", "display_name": "University of Massachusetts Amherst", "ror": "https://ror.org/0072zz521", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I24603500"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Andrew McCallum", "raw_affiliation_strings": ["University of Massachusetts, Amherst, MA"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Massachusetts, Amherst, MA", "institution_ids": ["https://openalex.org/I24603500"]}]}], "institutions": [], "countries_distinct_count": 1, "institutions_distinct_count": 1, "corresponding_author_ids": [], "corresponding_institution_ids": ["https://openalex.org/I24603500"], "apc_list": null, "apc_paid": null, "fwci": null, "has_fulltext": true, "cited_by_count": 746, "citation_normalized_percentile": null, "cited_by_percentile_year": null, "biblio": {"volume": null, "issue": null, "first_page": "99", "last_page": "99"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9994999766349792, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9994999766349792, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T11303", "display_name": "Bayesian Modeling and Causal Inference", "score": 0.9994999766349792, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 0.9983000159263611, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/crfs", "display_name": "CRFS", "score": 0.8942981958389282}, {"id": "https://openalex.org/keywords/conditional-random-field", "display_name": "Conditional random field", "score": 0.8288464546203613}, {"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.7172502279281616}, {"id": "https://openalex.org/keywords/inference", "display_name": "Inference", "score": 0.6483141779899597}, {"id": "https://openalex.org/keywords/approximate-inference", "display_name": "Approximate inference", "score": 0.5872994661331177}, {"id": "https://openalex.org/keywords/sequence-labeling", "display_name": "Sequence labeling", "score": 0.5776028633117676}, {"id": "https://openalex.org/keywords/belief-propagation", "display_name": "Belief propagation", "score": 0.5640208721160889}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.5415785908699036}, {"id": "https://openalex.org/keywords/dynamic-bayesian-network", "display_name": "Dynamic Bayesian network", "score": 0.4856971204280853}, {"id": "https://openalex.org/keywords/chain-rule", "display_name": "Chain rule (probability)", "score": 0.4824707806110382}, {"id": "https://openalex.org/keywords/generalization", "display_name": "Generalization", "score": 0.44046974182128906}, {"id": "https://openalex.org/keywords/sequence", "display_name": "Sequence (biology)", "score": 0.4321005940437317}, {"id": "https://openalex.org/keywords/bayesian-inference", "display_name": "Bayesian inference", "score": 0.43050479888916016}, {"id": "https://openalex.org/keywords/bayesian-network", "display_name": "Bayesian network", "score": 0.3921331465244293}, {"id": "https://openalex.org/keywords/algorithm", "display_name": "Algorithm", "score": 0.39011886715888977}, {"id": "https://openalex.org/keywords/machine-learning", "display_name": "Machine learning", "score": 0.38904455304145813}, {"id": "https://openalex.org/keywords/bayesian-probability", "display_name": "Bayesian probability", "score": 0.31008198857307434}, {"id": "https://openalex.org/keywords/posterior-probability", "display_name": "Posterior probability", "score": 0.2429296374320984}, {"id": "https://openalex.org/keywords/task", "display_name": "Task (project management)", "score": 0.24034619331359863}, {"id": "https://openalex.org/keywords/mathematics", "display_name": "Mathematics", "score": 0.2068743109703064}, {"id": "https://openalex.org/keywords/decoding-methods", "display_name": "Decoding methods", "score": 0.12934821844100952}, {"id": "https://openalex.org/keywords/regular-conditional-probability", "display_name": "Regular conditional probability", "score": 0.10678324103355408}], "concepts": [{"id": "https://openalex.org/C2775953691", "wikidata": "https://www.wikidata.org/wiki/Q5013874", "display_name": "CRFS", "level": 3, "score": 0.8942981958389282}, {"id": "https://openalex.org/C152565575", "wikidata": "https://www.wikidata.org/wiki/Q1124538", "display_name": "Conditional random field", "level": 2, "score": 0.8288464546203613}, {"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.7172502279281616}, {"id": "https://openalex.org/C2776214188", "wikidata": "https://www.wikidata.org/wiki/Q408386", "display_name": "Inference", "level": 2, "score": 0.6483141779899597}, {"id": "https://openalex.org/C2777472644", "wikidata": "https://www.wikidata.org/wiki/Q16968992", "display_name": "Approximate inference", "level": 3, "score": 0.5872994661331177}, {"id": "https://openalex.org/C35639132", "wikidata": "https://www.wikidata.org/wiki/Q7452468", "display_name": "Sequence labeling", "level": 3, "score": 0.5776028633117676}, {"id": "https://openalex.org/C152948882", "wikidata": "https://www.wikidata.org/wiki/Q4060686", "display_name": "Belief propagation", "level": 3, "score": 0.5640208721160889}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.5415785908699036}, {"id": "https://openalex.org/C82142266", "wikidata": "https://www.wikidata.org/wiki/Q3456604", "display_name": "Dynamic Bayesian network", "level": 3, "score": 0.4856971204280853}, {"id": "https://openalex.org/C33825631", "wikidata": "https://www.wikidata.org/wiki/Q17004731", "display_name": "Chain rule (probability)", "level": 5, "score": 0.4824707806110382}, {"id": "https://openalex.org/C177148314", "wikidata": "https://www.wikidata.org/wiki/Q170084", "display_name": "Generalization", "level": 2, "score": 0.44046974182128906}, {"id": "https://openalex.org/C2778112365", "wikidata": "https://www.wikidata.org/wiki/Q3511065", "display_name": "Sequence (biology)", "level": 2, "score": 0.4321005940437317}, {"id": "https://openalex.org/C160234255", "wikidata": "https://www.wikidata.org/wiki/Q812535", "display_name": "Bayesian inference", "level": 3, "score": 0.43050479888916016}, {"id": "https://openalex.org/C33724603", "wikidata": "https://www.wikidata.org/wiki/Q812540", "display_name": "Bayesian network", "level": 2, "score": 0.3921331465244293}, {"id": "https://openalex.org/C11413529", "wikidata": "https://www.wikidata.org/wiki/Q8366", "display_name": "Algorithm", "level": 1, "score": 0.39011886715888977}, {"id": "https://openalex.org/C119857082", "wikidata": "https://www.wikidata.org/wiki/Q2539", "display_name": "Machine learning", "level": 1, "score": 0.38904455304145813}, {"id": "https://openalex.org/C107673813", "wikidata": "https://www.wikidata.org/wiki/Q812534", "display_name": "Bayesian probability", "level": 2, "score": 0.31008198857307434}, {"id": "https://openalex.org/C57830394", "wikidata": "https://www.wikidata.org/wiki/Q278079", "display_name": "Posterior probability", "level": 3, "score": 0.2429296374320984}, {"id": "https://openalex.org/C2780451532", "wikidata": "https://www.wikidata.org/wiki/Q759676", "display_name": "Task (project management)", "level": 2, "score": 0.24034619331359863}, {"id": "https://openalex.org/C33923547", "wikidata": "https://www.wikidata.org/wiki/Q395", "display_name": "Mathematics", "level": 0, "score": 0.2068743109703064}, {"id": "https://openalex.org/C57273362", "wikidata": "https://www.wikidata.org/wiki/Q576722", "display_name": "Decoding methods", "level": 2, "score": 0.12934821844100952}, {"id": "https://openalex.org/C103982235", "wikidata": "https://www.wikidata.org/wiki/Q7309594", "display_name": "Regular conditional probability", "level": 4, "score": 0.10678324103355408}, {"id": "https://openalex.org/C134306372", "wikidata": "https://www.wikidata.org/wiki/Q7754", "display_name": "Mathematical analysis", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C162324750", "wikidata": "https://www.wikidata.org/wiki/Q8134", "display_name": "Economics", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C54355233", "wikidata": "https://www.wikidata.org/wiki/Q7162", "display_name": "Genetics", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C86803240", "wikidata": "https://www.wikidata.org/wiki/Q420", "display_name": "Biology", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C187736073", "wikidata": "https://www.wikidata.org/wiki/Q2920921", "display_name": "Management", "level": 1, "score": 0.0}], "mesh": [], "locations_count": 2, "locations": [{"id": "doi:10.1145/1015330.1015422", "is_oa": false, "landing_page_url": "https://doi.org/10.1145/1015330.1015422", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Twenty-first international conference on Machine learning - ICML '04", "raw_type": "proceedings-article"}, {"id": "pmh:oai:pure.ed.ac.uk:publications/91858f91-5ed1-49d6-9aeb-1c1a9a1e1e40", "is_oa": true, "landing_page_url": "http://doi.acm.org/10.1145/1015330.1015422", "pdf_url": "https://www.pure.ed.ac.uk/ws/files/14899616/p308_sutton.pdf", "source": {"id": "https://openalex.org/S4406922455", "display_name": "Edinburgh Research Explorer", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": null, "host_organization_name": null, "host_organization_lineage": [], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "", "raw_type": ""}], "best_oa_location": {"id": "pmh:oai:pure.ed.ac.uk:publications/91858f91-5ed1-49d6-9aeb-1c1a9a1e1e40", "is_oa": true, "landing_page_url": "http://doi.acm.org/10.1145/1015330.1015422", "pdf_url": "https://www.pure.ed.ac.uk/ws/files/14899616/p308_sutton.pdf", "source": {"id": "https://openalex.org/S4406922455", "display_name": "Edinburgh Research Explorer", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": null, "host_organization_name": null, "host_organization_lineage": [], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "", "raw_type": ""}, "sustainable_development_goals": [], "awards": [{"id": "https://openalex.org/G5318280894", "display_name": null, "funder_award_id": "NBCHD030010", "funder_id": "https://openalex.org/F4320306116", "funder_display_name": "U.S. Department of the Interior"}, {"id": "https://openalex.org/G730876220", "display_name": null, "funder_award_id": "NBCHD-03-0010", "funder_id": "https://openalex.org/F4320332180", "funder_display_name": "Defense Advanced Research Projects Agency"}, {"id": "https://openalex.org/G7704502625", "display_name": "ITR:     Unified Graphical Models of Information Extraction and Data Mining with Application to Social Network Analysis", "funder_award_id": "0326249", "funder_id": "https://openalex.org/F4320306076", "funder_display_name": "National Science Foundation"}], "funders": [{"id": "https://openalex.org/F4320306076", "display_name": "National Science Foundation", "ror": "https://ror.org/021nxhr62"}, {"id": "https://openalex.org/F4320306116", "display_name": "U.S. Department of the Interior", "ror": "https://ror.org/03v0pmy70"}, {"id": "https://openalex.org/F4320311089", "display_name": "National Security Agency", "ror": "https://ror.org/0047bvr32"}, {"id": "https://openalex.org/F4320332180", "display_name": "Defense Advanced Research Projects Agency", "ror": "https://ror.org/02caytj08"}, {"id": "https://openalex.org/F4320332815", "display_name": "Advanced Research Projects Agency", "ror": "https://ror.org/02caytj08"}], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2158823144.pdf", "grobid_xml": "https://content.openalex.org/works/W2158823144.grobid-xml"}, "referenced_works_count": 62, "referenced_works": ["https://openalex.org/W147273232", "https://openalex.org/W1499578805", "https://openalex.org/W1515272691", "https://openalex.org/W1526729636", "https://openalex.org/W1528056001", "https://openalex.org/W1530235965", "https://openalex.org/W1534730506", "https://openalex.org/W1560512119", "https://openalex.org/W1574901103", "https://openalex.org/W1578057148", "https://openalex.org/W1601974683", "https://openalex.org/W1604803556", "https://openalex.org/W1623072288", "https://openalex.org/W1632114991", "https://openalex.org/W1636244751", "https://openalex.org/W1732623802", "https://openalex.org/W1773803948", "https://openalex.org/W1934019294", "https://openalex.org/W1988995507", "https://openalex.org/W1999595522", "https://openalex.org/W2008652694", "https://openalex.org/W2020294948", "https://openalex.org/W2034797903", "https://openalex.org/W2041522124", "https://openalex.org/W2046932483", "https://openalex.org/W2095844239", "https://openalex.org/W2096044236", "https://openalex.org/W2096071754", "https://openalex.org/W2096175520", "https://openalex.org/W2098678088", "https://openalex.org/W2098921539", "https://openalex.org/W2102667697", "https://openalex.org/W2105644991", "https://openalex.org/W2110575115", "https://openalex.org/W2114521167", "https://openalex.org/W2116064496", "https://openalex.org/W2116410915", "https://openalex.org/W2118029084", "https://openalex.org/W2125838338", "https://openalex.org/W2137650255", "https://openalex.org/W2139686264", "https://openalex.org/W2143349571", "https://openalex.org/W2146143523", "https://openalex.org/W2147880316", "https://openalex.org/W2148160361", "https://openalex.org/W2151322733", "https://openalex.org/W2155925463", "https://openalex.org/W2156515921", "https://openalex.org/W2162340487", "https://openalex.org/W2163518744", "https://openalex.org/W2163915185", "https://openalex.org/W2164450870", "https://openalex.org/W2169415915", "https://openalex.org/W2949108231", "https://openalex.org/W2951299559", "https://openalex.org/W2951562155", "https://openalex.org/W2962735828", "https://openalex.org/W3104119384", "https://openalex.org/W4244018879", "https://openalex.org/W4244046749", "https://openalex.org/W4245655784", "https://openalex.org/W4253573210"], "related_works": ["https://openalex.org/W3015678144", "https://openalex.org/W2962906565", "https://openalex.org/W2798423868", "https://openalex.org/W142195158", "https://openalex.org/W2963575689", "https://openalex.org/W2752313418", "https://openalex.org/W2076440176", "https://openalex.org/W4297478883", "https://openalex.org/W1595840999", "https://openalex.org/W2158823144"], "abstract_inverted_index": {"In": [0], "sequence": [1], "modeling,": [2], "we": [3, 80, 99], "often": [4], "wish": [5], "to": [6], "represent": [7], "complex": [8], "interaction": [9], "between": [10], "labels,": [11], "such": [12, 78], "as": [13, 60], "when": [14, 25], "performing": [15], "multiple,": [16], "cascaded": [17], "labeling": [18], "tasks": [19], "on": [20], "the": [21, 118], "same": [22], "sequence,": [23], "or": [24], "long-range": [26], "dependencies": [27], "exist.": [28], "We": [29], "present": [30], "dynamic": [31, 62], "conditional": [32, 40], "random": [33, 41], "fields": [34, 42], "(DCRFs),": [35], "a": [36, 50, 95, 102, 107], "generalization": [37], "of": [38, 52, 109], "linear-chain": [39, 110], "(CRFs)": [43], "in": [44, 61, 77], "which": [45], "each": [46], "time": [47], "slice": [48], "contains": [49], "set": [51], "state": [53, 58], "variables": [54], "and": [55], "edges---a": [56], "distributed": [57], "representation": [59], "Bayesian": [63], "networks": [64], "(DBNs)---and": [65], "parameters": [66], "are": [67], "tied": [68], "across": [69], "slices.": [70], "Since": [71], "exact": [72], "inference": [73, 83], "can": [74], "be": [75], "intractable": [76], "models,": [79], "perform": [81], "approximate": [82], "using": [84, 115], "several": [85], "schedules": [86], "for": [87], "belief": [88], "propagation,": [89], "including": [90], "tree-based": [91], "reparameterization": [92], "(TRP).": [93], "On": [94], "natural-language": [96], "chunking": [97], "task,": [98], "show": [100], "that": [101], "DCRF": [103], "performs": [104], "better": [105], "than": [106], "series": [108], "CRFs,": [111], "achieving": [112], "comparable": [113], "performance": [114], "only": [116], "half": [117], "training": [119], "data.": [120]}, "counts_by_year": [{"year": 2026, "cited_by_count": 1}, {"year": 2025, "cited_by_count": 8}, {"year": 2024, "cited_by_count": 11}, {"year": 2023, "cited_by_count": 13}, {"year": 2022, "cited_by_count": 10}, {"year": 2021, "cited_by_count": 14}, {"year": 2020, "cited_by_count": 28}, {"year": 2019, "cited_by_count": 15}, {"year": 2018, "cited_by_count": 11}, {"year": 2017, "cited_by_count": 7}, {"year": 2016, "cited_by_count": 14}, {"year": 2015, "cited_by_count": 31}, {"year": 2014, "cited_by_count": 63}, {"year": 2013, "cited_by_count": 64}, {"year": 2012, "cited_by_count": 53}], "updated_date": "2026-08-01T09:00:35.917206", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W2141099517", "doi": "https://doi.org/10.3115/1119176.1119206", "title": "Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons", "display_name": "Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons", "relevance_score": 858.7629, "publication_year": 2003, "publication_date": "2003-01-01", "ids": {"openalex": "https://openalex.org/W2141099517", "doi": "https://doi.org/10.3115/1119176.1119206", "mag": "2141099517"}, "language": "en", "primary_location": {"id": "doi:10.3115/1119176.1119206", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1119176.1119206", "pdf_url": "https://dl.acm.org/doi/pdf/10.3115/1119176.1119206", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 -", "raw_type": "proceedings-article"}, "type": "conference-paper", "indexed_in": ["crossref"], "open_access": {"is_oa": true, "oa_status": "gold", "oa_url": "https://dl.acm.org/doi/pdf/10.3115/1119176.1119206", "any_repository_has_fulltext": null}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5107835063", "display_name": "Andrew McCallum", "orcid": null}, "institutions": [{"id": "https://openalex.org/I24603500", "display_name": "University of Massachusetts Amherst", "ror": "https://ror.org/0072zz521", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I24603500"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Andrew McCallum", "raw_affiliation_strings": ["University of Massachusetts Amherst, Amherst, MA", "University of Massachusetts Amherst Amherst, MA"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Massachusetts Amherst, Amherst, MA", "institution_ids": ["https://openalex.org/I24603500"]}, {"raw_affiliation_string": "University of Massachusetts Amherst Amherst, MA", "institution_ids": ["https://openalex.org/I24603500"]}]}, {"author_position": "last", "author": {"id": "https://openalex.org/A5045547813", "display_name": "Wei Li", "orcid": "https://orcid.org/0000-0002-2250-2031"}, "institutions": [{"id": "https://openalex.org/I24603500", "display_name": "University of Massachusetts Amherst", "ror": "https://ror.org/0072zz521", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I24603500"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Wei Li", "raw_affiliation_strings": ["University of Massachusetts Amherst, Amherst, MA", "University of Massachusetts Amherst Amherst, MA"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Massachusetts Amherst, Amherst, MA", "institution_ids": ["https://openalex.org/I24603500"]}, {"raw_affiliation_string": "University of Massachusetts Amherst Amherst, MA", "institution_ids": ["https://openalex.org/I24603500"]}]}], "institutions": [], "countries_distinct_count": 1, "institutions_distinct_count": 1, "corresponding_author_ids": [], "corresponding_institution_ids": ["https://openalex.org/I24603500"], "apc_list": null, "apc_paid": null, "fwci": 17.8692, "has_fulltext": true, "cited_by_count": 1164, "citation_normalized_percentile": {"value": 0.99592425, "is_in_top_1_percent": true, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 99, "max": 100}, "biblio": {"volume": "4", "issue": null, "first_page": "188", "last_page": "191"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9998999834060669, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9998999834060669, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 0.9998999834060669, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T11710", "display_name": "Biomedical Text Mining and Ontologies", "score": 0.98089998960495, "subfield": {"id": "https://openalex.org/subfields/1312", "display_name": "Molecular Biology"}, "field": {"id": "https://openalex.org/fields/13", "display_name": "Biochemistry, Genetics and Molecular Biology"}, "domain": {"id": "https://openalex.org/domains/1", "display_name": "Life Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/conditional-random-field", "display_name": "Conditional random field", "score": 0.8916435241699219}, {"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.7834206819534302}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.647213339805603}, {"id": "https://openalex.org/keywords/natural-language-processing", "display_name": "Natural language processing", "score": 0.5872430801391602}, {"id": "https://openalex.org/keywords/probabilistic-logic", "display_name": "Probabilistic logic", "score": 0.5373998880386353}, {"id": "https://openalex.org/keywords/principle-of-maximum-entropy", "display_name": "Principle of maximum entropy", "score": 0.5331764817237854}, {"id": "https://openalex.org/keywords/language-model", "display_name": "Language model", "score": 0.5016384124755859}, {"id": "https://openalex.org/keywords/generative-grammar", "display_name": "Generative grammar", "score": 0.5006551742553711}, {"id": "https://openalex.org/keywords/word", "display_name": "Word (group theory)", "score": 0.4973619282245636}, {"id": "https://openalex.org/keywords/named-entity-recognition", "display_name": "Named-entity recognition", "score": 0.4778549373149872}, {"id": "https://openalex.org/keywords/statistical-model", "display_name": "Statistical model", "score": 0.4540099501609802}, {"id": "https://openalex.org/keywords/feature", "display_name": "Feature (linguistics)", "score": 0.41435906291007996}, {"id": "https://openalex.org/keywords/generative-model", "display_name": "Generative model", "score": 0.4122285842895508}, {"id": "https://openalex.org/keywords/mathematics", "display_name": "Mathematics", "score": 0.09912821650505066}], "concepts": [{"id": "https://openalex.org/C152565575", "wikidata": "https://www.wikidata.org/wiki/Q1124538", "display_name": "Conditional random field", "level": 2, "score": 0.8916435241699219}, {"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.7834206819534302}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.647213339805603}, {"id": "https://openalex.org/C204321447", "wikidata": "https://www.wikidata.org/wiki/Q30642", "display_name": "Natural language processing", "level": 1, "score": 0.5872430801391602}, {"id": "https://openalex.org/C49937458", "wikidata": "https://www.wikidata.org/wiki/Q2599292", "display_name": "Probabilistic logic", "level": 2, "score": 0.5373998880386353}, {"id": "https://openalex.org/C9679016", "wikidata": "https://www.wikidata.org/wiki/Q1417473", "display_name": "Principle of maximum entropy", "level": 2, "score": 0.5331764817237854}, {"id": "https://openalex.org/C137293760", "wikidata": "https://www.wikidata.org/wiki/Q3621696", "display_name": "Language model", "level": 2, "score": 0.5016384124755859}, {"id": "https://openalex.org/C39890363", "wikidata": "https://www.wikidata.org/wiki/Q36108", "display_name": "Generative grammar", "level": 2, "score": 0.5006551742553711}, {"id": "https://openalex.org/C90805587", "wikidata": "https://www.wikidata.org/wiki/Q10944557", "display_name": "Word (group theory)", "level": 2, "score": 0.4973619282245636}, {"id": "https://openalex.org/C2779135771", "wikidata": "https://www.wikidata.org/wiki/Q403574", "display_name": "Named-entity recognition", "level": 3, "score": 0.4778549373149872}, {"id": "https://openalex.org/C114289077", "wikidata": "https://www.wikidata.org/wiki/Q3284399", "display_name": "Statistical model", "level": 2, "score": 0.4540099501609802}, {"id": "https://openalex.org/C2776401178", "wikidata": "https://www.wikidata.org/wiki/Q12050496", "display_name": "Feature (linguistics)", "level": 2, "score": 0.41435906291007996}, {"id": "https://openalex.org/C167966045", "wikidata": "https://www.wikidata.org/wiki/Q5532625", "display_name": "Generative model", "level": 3, "score": 0.4122285842895508}, {"id": "https://openalex.org/C33923547", "wikidata": "https://www.wikidata.org/wiki/Q395", "display_name": "Mathematics", "level": 0, "score": 0.09912821650505066}, {"id": "https://openalex.org/C162324750", "wikidata": "https://www.wikidata.org/wiki/Q8134", "display_name": "Economics", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C41895202", "wikidata": "https://www.wikidata.org/wiki/Q8162", "display_name": "Linguistics", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C138885662", "wikidata": "https://www.wikidata.org/wiki/Q5891", "display_name": "Philosophy", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C2780451532", "wikidata": "https://www.wikidata.org/wiki/Q759676", "display_name": "Task (project management)", "level": 2, "score": 0.0}, {"id": "https://openalex.org/C187736073", "wikidata": "https://www.wikidata.org/wiki/Q2920921", "display_name": "Management", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C2524010", "wikidata": "https://www.wikidata.org/wiki/Q8087", "display_name": "Geometry", "level": 1, "score": 0.0}], "mesh": [], "locations_count": 8, "locations": [{"id": "doi:10.3115/1119176.1119206", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1119176.1119206", "pdf_url": "https://dl.acm.org/doi/pdf/10.3115/1119176.1119206", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 -", "raw_type": "proceedings-article"}, {"id": "pmh:oai:scholarworks.umass.edu:cs_faculty_pubs-1014", "is_oa": false, "landing_page_url": "https://scholarworks.umass.edu/cs_faculty_pubs/11", "pdf_url": null, "source": {"id": "https://openalex.org/S4306402240", "display_name": "ScholarWorks@UMassAmherst (University of Massachusetts Amherst)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I24603500", "host_organization_name": "University of Massachusetts Amherst", "host_organization_lineage": ["https://openalex.org/I24603500"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Computer Science Department Faculty Publication Series", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.14.7963", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.7963", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cs.umass.edu/~mccallum/papers/mccallum-conll2003.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.3.6795", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.3.6795", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://acl.ldc.upenn.edu/W/W03/W03-0430.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.4.7233", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.4.7233", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://cnts.uia.ac.be/conll2003/ps/18891mcc.ps.gz", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.457.668", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.457.668", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://clair.si.umich.edu/clair/HLT-NAACL03/conll/pdf/mccallum.pdf", "raw_type": "text"}, {"id": "pmh:oai:scholarworks.umass.edu:20.500.14394/9595", "is_oa": false, "landing_page_url": "https://hdl.handle.net/20.500.14394/9595", "pdf_url": null, "source": {"id": "https://openalex.org/S4306402057", "display_name": "Scholarworks (University of Massachusetts Amherst)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I24603500", "host_organization_name": "University of Massachusetts Amherst", "host_organization_lineage": ["https://openalex.org/I24603500"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "published", "raw_type": "Article"}, {"id": "pmh:oai:works.bepress.com:andrew_mccallum-1002", "is_oa": false, "landing_page_url": "https://works.bepress.com/andrew_mccallum/3", "pdf_url": null, "source": {"id": "https://openalex.org/S4306402240", "display_name": "ScholarWorks@UMassAmherst (University of Massachusetts Amherst)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I24603500", "host_organization_name": "University of Massachusetts Amherst", "host_organization_lineage": ["https://openalex.org/I24603500"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Andrew McCallum", "raw_type": "text"}], "best_oa_location": {"id": "doi:10.3115/1119176.1119206", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1119176.1119206", "pdf_url": "https://dl.acm.org/doi/pdf/10.3115/1119176.1119206", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 -", "raw_type": "proceedings-article"}, "sustainable_development_goals": [], "awards": [], "funders": [{"id": "https://openalex.org/F4320332180", "display_name": "Defense Advanced Research Projects Agency", "ror": "https://ror.org/02caytj08"}], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2141099517.pdf", "grobid_xml": "https://content.openalex.org/works/W2141099517.grobid-xml"}, "referenced_works_count": 10, "referenced_works": ["https://openalex.org/W589407005", "https://openalex.org/W1575332430", "https://openalex.org/W1773803948", "https://openalex.org/W2102667697", "https://openalex.org/W2139193890", "https://openalex.org/W2147880316", "https://openalex.org/W2156515921", "https://openalex.org/W2160842254", "https://openalex.org/W2612120747", "https://openalex.org/W2785349534"], "related_works": ["https://openalex.org/W4250494529", "https://openalex.org/W1964783010", "https://openalex.org/W2399696375", "https://openalex.org/W45206245", "https://openalex.org/W2211396092", "https://openalex.org/W2061834489", "https://openalex.org/W3088215229", "https://openalex.org/W2078793151", "https://openalex.org/W3047727388", "https://openalex.org/W2759598007"], "abstract_inverted_index": {"Models": [0], "for": [1, 19, 78], "many": [2], "natural": [3], "language": [4], "tasks": [5], "benefit": [6], "from": [7], "the": [8, 17, 33], "flexibility": [9], "to": [10, 49], "use": [11], "overlapping,": [12], "non-independent": [13], "features.": [14], "For": [15], "example,": [16], "need": [18], "labeled": [20], "data": [21], "can": [22], "be": [23], "drastically": [24], "reduced": [25], "by": [26], "taking": [27], "advantage": [28], "of": [29, 35], "domain": [30], "knowledge": [31], "in": [32, 82], "form": [34], "word": [36], "lists,": [37], "part-of-speech": [38], "tags,": [39], "character": [40], "n-grams,": [41], "and": [42], "capitalization": [43], "patterns.": [44], "While": [45], "it": [46], "is": [47], "difficult": [48], "capture": [50], "such": [51, 61, 76], "inter-dependent": [52], "features": [53], "with": [54, 75], "a": [55], "generative": [56], "probabilistic": [57], "model,": [58], "conditionally-trained": [59], "models,": [60, 66], "as": [62], "conditional": [63], "maximum": [64], "entropy": [65], "handle": [67], "them": [68], "well.": [69], "There": [70], "has": [71], "been": [72], "significant": [73], "work": [74], "models": [77], "greedy": [79], "sequence": [80], "modeling": [81], "NLP": [83], "(Ratnaparkhi,": [84], "1996;": [85], "Borthwick": [86], "et": [87], "al.,": [88], "1998).": [89]}, "counts_by_year": [{"year": 2026, "cited_by_count": 9}, {"year": 2025, "cited_by_count": 14}, {"year": 2024, "cited_by_count": 35}, {"year": 2023, "cited_by_count": 52}, {"year": 2022, "cited_by_count": 49}, {"year": 2021, "cited_by_count": 77}, {"year": 2020, "cited_by_count": 77}, {"year": 2019, "cited_by_count": 82}, {"year": 2018, "cited_by_count": 72}, {"year": 2017, "cited_by_count": 76}, {"year": 2016, "cited_by_count": 58}, {"year": 2015, "cited_by_count": 68}, {"year": 2014, "cited_by_count": 63}, {"year": 2013, "cited_by_count": 75}, {"year": 2012, "cited_by_count": 74}], "updated_date": "2026-08-01T09:00:35.917206", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W1992419399", "doi": "https://doi.org/10.1145/331499.331504", "title": "Data clustering", "display_name": "Data clustering", "relevance_score": 841.1856, "publication_year": 1999, "publication_date": "1999-09-01", "ids": {"openalex": "https://openalex.org/W1992419399", "doi": "https://doi.org/10.1145/331499.331504", "mag": "1992419399"}, "language": "en", "primary_location": {"id": "doi:10.1145/331499.331504", "is_oa": true, "landing_page_url": "https://doi.org/10.1145/331499.331504", "pdf_url": "https://dl.acm.org/doi/pdf/10.1145/331499.331504", "source": {"id": "https://openalex.org/S157921468", "display_name": "ACM Computing Surveys", "issn_l": "0360-0300", "issn": ["0360-0300", "1557-7341"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310319798", "host_organization_name": "Association for Computing Machinery", "host_organization_lineage": ["https://openalex.org/P4310319798"], "host_organization_lineage_names": ["Association for Computing Machinery"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "ACM Computing Surveys", "raw_type": "journal-article"}, "type": "article", "indexed_in": ["crossref"], "open_access": {"is_oa": true, "oa_status": "bronze", "oa_url": "https://dl.acm.org/doi/pdf/10.1145/331499.331504", "any_repository_has_fulltext": false}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5100613677", "display_name": "Anil K. Jain", "orcid": "https://orcid.org/0000-0002-6369-6995"}, "institutions": [{"id": "https://openalex.org/I87216513", "display_name": "Michigan State University", "ror": "https://ror.org/05hs6h993", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I87216513"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "A. K. Jain", "raw_affiliation_strings": ["Michigan State Univ., East Lansing", "Michigan State Univ., East Lansing#TAB#"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Michigan State Univ., East Lansing", "institution_ids": ["https://openalex.org/I87216513"]}, {"raw_affiliation_string": "Michigan State Univ., East Lansing#TAB#", "institution_ids": ["https://openalex.org/I87216513"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5028996052", "display_name": "M. Narasimha Murty", "orcid": null}, "institutions": [{"id": "https://openalex.org/I59270414", "display_name": "Indian Institute of Science Bangalore", "ror": "https://ror.org/04dese585", "country_code": "IN", "type": "education", "lineage": ["https://openalex.org/I59270414"]}], "countries": ["IN"], "is_corresponding": false, "raw_author_name": "M. N. Murty", "raw_affiliation_strings": ["Indian Institute of Science, Bangalore, India"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Indian Institute of Science, Bangalore, India", "institution_ids": ["https://openalex.org/I59270414"]}]}, {"author_position": "last", "author": {"id": "https://openalex.org/A5039987576", "display_name": "Patrick J. Flynn", "orcid": "https://orcid.org/0000-0002-5446-114X"}, "institutions": [{"id": "https://openalex.org/I52357470", "display_name": "The Ohio State University", "ror": "https://ror.org/00rs6vg23", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I52357470"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "P. J. Flynn", "raw_affiliation_strings": ["Ohio State Univ., Columbus", "Ohio State Univ., Columbus#TAB#"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Ohio State Univ., Columbus", "institution_ids": ["https://openalex.org/I52357470"]}, {"raw_affiliation_string": "Ohio State Univ., Columbus#TAB#", "institution_ids": ["https://openalex.org/I52357470"]}]}], "institutions": [], "countries_distinct_count": 2, "institutions_distinct_count": 3, "corresponding_author_ids": [], "corresponding_institution_ids": [], "apc_list": null, "apc_paid": null, "fwci": 92.9222, "has_fulltext": true, "cited_by_count": 13234, "citation_normalized_percentile": {"value": 0.99976436, "is_in_top_1_percent": true, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 99, "max": 100}, "biblio": {"volume": "31", "issue": "3", "first_page": "264", "last_page": "323"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10637", "display_name": "Advanced Clustering Algorithms Research", "score": 0.9987999796867371, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10637", "display_name": "Advanced Clustering Algorithms Research", "score": 0.9987999796867371, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10824", "display_name": "Image Retrieval and Classification Techniques", "score": 0.9987999796867371, "subfield": {"id": "https://openalex.org/subfields/1707", "display_name": "Computer Vision and Pattern Recognition"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T11106", "display_name": "Data Management and Algorithms", "score": 0.9976000189781189, "subfield": {"id": "https://openalex.org/subfields/1711", "display_name": "Signal Processing"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/cluster-analysis", "display_name": "Cluster analysis", "score": 0.874695360660553}, {"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.8398610353469849}, {"id": "https://openalex.org/keywords/conceptual-clustering", "display_name": "Conceptual clustering", "score": 0.5918213725090027}, {"id": "https://openalex.org/keywords/consensus-clustering", "display_name": "Consensus clustering", "score": 0.5891347527503967}, {"id": "https://openalex.org/keywords/fuzzy-clustering", "display_name": "Fuzzy clustering", "score": 0.5438249111175537}, {"id": "https://openalex.org/keywords/perspective", "display_name": "Perspective (graphical)", "score": 0.47377681732177734}, {"id": "https://openalex.org/keywords/biclustering", "display_name": "Biclustering", "score": 0.4576820433139801}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.457621693611145}, {"id": "https://openalex.org/keywords/data-mining", "display_name": "Data mining", "score": 0.4316200017929077}, {"id": "https://openalex.org/keywords/clustering-high-dimensional-data", "display_name": "Clustering high-dimensional data", "score": 0.41467708349227905}, {"id": "https://openalex.org/keywords/machine-learning", "display_name": "Machine learning", "score": 0.4002190828323364}, {"id": "https://openalex.org/keywords/information-retrieval", "display_name": "Information retrieval", "score": 0.343196839094162}, {"id": "https://openalex.org/keywords/cure-data-clustering-algorithm", "display_name": "CURE data clustering algorithm", "score": 0.3319856822490692}, {"id": "https://openalex.org/keywords/data-science", "display_name": "Data science", "score": 0.3237067461013794}], "concepts": [{"id": "https://openalex.org/C73555534", "wikidata": "https://www.wikidata.org/wiki/Q622825", "display_name": "Cluster analysis", "level": 2, "score": 0.874695360660553}, {"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.8398610353469849}, {"id": "https://openalex.org/C39235581", "wikidata": "https://www.wikidata.org/wiki/Q5158434", "display_name": "Conceptual clustering", "level": 5, "score": 0.5918213725090027}, {"id": "https://openalex.org/C186767784", "wikidata": "https://www.wikidata.org/wiki/Q5162841", "display_name": "Consensus clustering", "level": 5, "score": 0.5891347527503967}, {"id": "https://openalex.org/C17212007", "wikidata": "https://www.wikidata.org/wiki/Q5511111", "display_name": "Fuzzy clustering", "level": 3, "score": 0.5438249111175537}, {"id": "https://openalex.org/C12713177", "wikidata": "https://www.wikidata.org/wiki/Q1900281", "display_name": "Perspective (graphical)", "level": 2, "score": 0.47377681732177734}, {"id": "https://openalex.org/C144817290", "wikidata": "https://www.wikidata.org/wiki/Q2976575", "display_name": "Biclustering", "level": 5, "score": 0.4576820433139801}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.457621693611145}, {"id": "https://openalex.org/C124101348", "wikidata": "https://www.wikidata.org/wiki/Q172491", "display_name": "Data mining", "level": 1, "score": 0.4316200017929077}, {"id": "https://openalex.org/C184509293", "wikidata": "https://www.wikidata.org/wiki/Q5136711", "display_name": "Clustering high-dimensional data", "level": 3, "score": 0.41467708349227905}, {"id": "https://openalex.org/C119857082", "wikidata": "https://www.wikidata.org/wiki/Q2539", "display_name": "Machine learning", "level": 1, "score": 0.4002190828323364}, {"id": "https://openalex.org/C23123220", "wikidata": "https://www.wikidata.org/wiki/Q816826", "display_name": "Information retrieval", "level": 1, "score": 0.343196839094162}, {"id": "https://openalex.org/C33704608", "wikidata": "https://www.wikidata.org/wiki/Q5014717", "display_name": "CURE data clustering algorithm", "level": 4, "score": 0.3319856822490692}, {"id": "https://openalex.org/C2522767166", "wikidata": "https://www.wikidata.org/wiki/Q2374463", "display_name": "Data science", "level": 1, "score": 0.3237067461013794}], "mesh": [], "locations_count": 1, "locations": [{"id": "doi:10.1145/331499.331504", "is_oa": true, "landing_page_url": "https://doi.org/10.1145/331499.331504", "pdf_url": "https://dl.acm.org/doi/pdf/10.1145/331499.331504", "source": {"id": "https://openalex.org/S157921468", "display_name": "ACM Computing Surveys", "issn_l": "0360-0300", "issn": ["0360-0300", "1557-7341"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310319798", "host_organization_name": "Association for Computing Machinery", "host_organization_lineage": ["https://openalex.org/P4310319798"], "host_organization_lineage_names": ["Association for Computing Machinery"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "ACM Computing Surveys", "raw_type": "journal-article"}], "best_oa_location": {"id": "doi:10.1145/331499.331504", "is_oa": true, "landing_page_url": "https://doi.org/10.1145/331499.331504", "pdf_url": "https://dl.acm.org/doi/pdf/10.1145/331499.331504", "source": {"id": "https://openalex.org/S157921468", "display_name": "ACM Computing Surveys", "issn_l": "0360-0300", "issn": ["0360-0300", "1557-7341"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310319798", "host_organization_name": "Association for Computing Machinery", "host_organization_lineage": ["https://openalex.org/P4310319798"], "host_organization_lineage_names": ["Association for Computing Machinery"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "ACM Computing Surveys", "raw_type": "journal-article"}, "sustainable_development_goals": [], "awards": [{"id": "https://openalex.org/G68028425", "display_name": "Knowledge-based Clustering, Indo-U.S. Collaborative         Research.  Award In U.S. and Indian Currencies", "funder_award_id": "9321584", "funder_id": "https://openalex.org/F4320306076", "funder_display_name": "National Science Foundation"}], "funders": [{"id": "https://openalex.org/F4320306076", "display_name": "National Science Foundation", "ror": "https://ror.org/021nxhr62"}], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W1992419399.pdf", "grobid_xml": "https://content.openalex.org/works/W1992419399.grobid-xml"}, "referenced_works_count": 251, "referenced_works": ["https://openalex.org/W2589729", "https://openalex.org/W19698511", "https://openalex.org/W23758216", "https://openalex.org/W32845244", "https://openalex.org/W58767217", "https://openalex.org/W65197548", "https://openalex.org/W108464071", "https://openalex.org/W110614009", "https://openalex.org/W113318161", "https://openalex.org/W127942951", "https://openalex.org/W159579334", "https://openalex.org/W196505194", "https://openalex.org/W605211202", "https://openalex.org/W1480487340", "https://openalex.org/W1480633570", "https://openalex.org/W1486136840", "https://openalex.org/W1497256448", "https://openalex.org/W1498782169", "https://openalex.org/W1501657095", "https://openalex.org/W1511493290", "https://openalex.org/W1515824999", "https://openalex.org/W1528576675", "https://openalex.org/W1550725414", "https://openalex.org/W1558180172", "https://openalex.org/W1575476631", "https://openalex.org/W1598760490", "https://openalex.org/W1622235773", "https://openalex.org/W1622620102", "https://openalex.org/W1639032689", "https://openalex.org/W1770825568", "https://openalex.org/W1872445975", "https://openalex.org/W1968745451", "https://openalex.org/W1968840731", "https://openalex.org/W1969840923", "https://openalex.org/W1971279136", "https://openalex.org/W1971540165", "https://openalex.org/W1971784203", "https://openalex.org/W1972969203", "https://openalex.org/W1975149851", "https://openalex.org/W1976865007", "https://openalex.org/W1977516301", "https://openalex.org/W1977867644", "https://openalex.org/W1978627835", "https://openalex.org/W1979412257", "https://openalex.org/W1980909228", "https://openalex.org/W1982647060", "https://openalex.org/W1983311921", "https://openalex.org/W1985139833", "https://openalex.org/W1986266833", "https://openalex.org/W1987351746", "https://openalex.org/W1991848143", "https://openalex.org/W1992030530", "https://openalex.org/W1992081792", "https://openalex.org/W1995802550", "https://openalex.org/W1995872006", "https://openalex.org/W1996096452", "https://openalex.org/W1996261818", "https://openalex.org/W1996350342", "https://openalex.org/W1996773532", "https://openalex.org/W1997058150", "https://openalex.org/W1997152779", "https://openalex.org/W1997841190", "https://openalex.org/W1998514600", "https://openalex.org/W2000621731", "https://openalex.org/W2001302965", "https://openalex.org/W2001705674", "https://openalex.org/W2001850277", "https://openalex.org/W2002016471", "https://openalex.org/W2003004389", "https://openalex.org/W2003668590", "https://openalex.org/W2003677434", "https://openalex.org/W2004641810", "https://openalex.org/W2005852173", "https://openalex.org/W2006636107", "https://openalex.org/W2009696524", "https://openalex.org/W2014139125", "https://openalex.org/W2016381774", "https://openalex.org/W2018359542", "https://openalex.org/W2019273017", "https://openalex.org/W2019519548", "https://openalex.org/W2020735245", "https://openalex.org/W2021751319", "https://openalex.org/W2022686119", "https://openalex.org/W2024060531", "https://openalex.org/W2024276726", "https://openalex.org/W2024868117", "https://openalex.org/W2026577953", "https://openalex.org/W2028569720", "https://openalex.org/W2029952774", "https://openalex.org/W2030129920", "https://openalex.org/W2030647854", "https://openalex.org/W2030720628", "https://openalex.org/W2031586513", "https://openalex.org/W2033802199", "https://openalex.org/W2033849769", "https://openalex.org/W2034024435", "https://openalex.org/W2034562813", "https://openalex.org/W2035407230", "https://openalex.org/W2035420489", "https://openalex.org/W2036978226", "https://openalex.org/W2037591014", "https://openalex.org/W2038098542", "https://openalex.org/W2040179990", "https://openalex.org/W2040810017", "https://openalex.org/W2044520381", "https://openalex.org/W2045315420", "https://openalex.org/W2046953300", "https://openalex.org/W2049633694", "https://openalex.org/W2049694710", "https://openalex.org/W2050261677", "https://openalex.org/W2050547330", "https://openalex.org/W2051853955", "https://openalex.org/W2052351313", "https://openalex.org/W2056630909", "https://openalex.org/W2056658050", "https://openalex.org/W2057411438", "https://openalex.org/W2057691548", "https://openalex.org/W2058324463", "https://openalex.org/W2063295648", "https://openalex.org/W2065417009", "https://openalex.org/W2067878730", "https://openalex.org/W2067958620", "https://openalex.org/W2069610368", "https://openalex.org/W2070771945", "https://openalex.org/W2071106922", "https://openalex.org/W2072533619", "https://openalex.org/W2073308541", "https://openalex.org/W2073503732", "https://openalex.org/W2073568237", "https://openalex.org/W2073849744", "https://openalex.org/W2075690349", "https://openalex.org/W2077990749", "https://openalex.org/W2080847832", "https://openalex.org/W2082046852", "https://openalex.org/W2084792706", "https://openalex.org/W2089040534", "https://openalex.org/W2089923519", "https://openalex.org/W2090154563", "https://openalex.org/W2092977764", "https://openalex.org/W2095897464", "https://openalex.org/W2096832794", "https://openalex.org/W2102150301", "https://openalex.org/W2107105977", "https://openalex.org/W2113076747", "https://openalex.org/W2114545146", "https://openalex.org/W2118587067", "https://openalex.org/W2124957865", "https://openalex.org/W2127218421", "https://openalex.org/W2132603077", "https://openalex.org/W2133671888", "https://openalex.org/W2134312057", "https://openalex.org/W2135054260", "https://openalex.org/W2135346934", "https://openalex.org/W2135525489", "https://openalex.org/W2137199074", "https://openalex.org/W2138745909", "https://openalex.org/W2141807666", "https://openalex.org/W2142652670", "https://openalex.org/W2145069199", "https://openalex.org/W2148394752", "https://openalex.org/W2148539800", "https://openalex.org/W2149779626", "https://openalex.org/W2152150600", "https://openalex.org/W2152151913", "https://openalex.org/W2153649609", "https://openalex.org/W2155513645", "https://openalex.org/W2155687169", "https://openalex.org/W2156644018", "https://openalex.org/W2156771765", "https://openalex.org/W2157231347", "https://openalex.org/W2157709461", "https://openalex.org/W2160754664", "https://openalex.org/W2162765447", "https://openalex.org/W2163952039", "https://openalex.org/W2165202884", "https://openalex.org/W2166698530", "https://openalex.org/W2166843422", "https://openalex.org/W2168623285", "https://openalex.org/W2169132902", "https://openalex.org/W2169714917", "https://openalex.org/W2171124048", "https://openalex.org/W2171246116", "https://openalex.org/W2171612090", "https://openalex.org/W2172382511", "https://openalex.org/W2235047952", "https://openalex.org/W2299467264", "https://openalex.org/W2313094819", "https://openalex.org/W2327731342", "https://openalex.org/W2340480757", "https://openalex.org/W2432567885", "https://openalex.org/W2489342151", "https://openalex.org/W2612166593", "https://openalex.org/W2752853835", "https://openalex.org/W2752908210", "https://openalex.org/W2800728191", "https://openalex.org/W2801345297", "https://openalex.org/W2911854988", "https://openalex.org/W2912565176", "https://openalex.org/W2913066018", "https://openalex.org/W2913091258", "https://openalex.org/W2914866334", "https://openalex.org/W2915036154", "https://openalex.org/W2923626555", "https://openalex.org/W2953560884", "https://openalex.org/W3016023956", "https://openalex.org/W3016210511", "https://openalex.org/W3017143921", "https://openalex.org/W3021735434", "https://openalex.org/W3023540311", "https://openalex.org/W3036512766", "https://openalex.org/W3146675199", "https://openalex.org/W3149025087", "https://openalex.org/W4211007335", "https://openalex.org/W4213261160", "https://openalex.org/W4214561203", "https://openalex.org/W4231029117", "https://openalex.org/W4236431802", "https://openalex.org/W4236857239", "https://openalex.org/W4238135117", "https://openalex.org/W4242446209", "https://openalex.org/W4244075810", "https://openalex.org/W4255733600", "https://openalex.org/W4298069009", "https://openalex.org/W4299445015", "https://openalex.org/W4300569042", "https://openalex.org/W4302050201", "https://openalex.org/W6600102665", "https://openalex.org/W6602397713", "https://openalex.org/W6606476859", "https://openalex.org/W6628813422", "https://openalex.org/W6629948192", "https://openalex.org/W6636574509", "https://openalex.org/W6636620950", "https://openalex.org/W6645391629", "https://openalex.org/W6648197129", "https://openalex.org/W6667659371", "https://openalex.org/W6677796945", "https://openalex.org/W6680086184", "https://openalex.org/W6698813454", "https://openalex.org/W6704190477", "https://openalex.org/W6721827378", "https://openalex.org/W6732068779", "https://openalex.org/W6738852829", "https://openalex.org/W6744529318", "https://openalex.org/W6770641979", "https://openalex.org/W6776565550", "https://openalex.org/W6806421124", "https://openalex.org/W6806911829", "https://openalex.org/W6993059093", "https://openalex.org/W7062157157", "https://openalex.org/W7073939800"], "related_works": ["https://openalex.org/W2111827030", "https://openalex.org/W2611629964", "https://openalex.org/W4237106426", "https://openalex.org/W3035964814", "https://openalex.org/W2311450085", "https://openalex.org/W2107260502", "https://openalex.org/W3168918549", "https://openalex.org/W4232587025", "https://openalex.org/W3020292803", "https://openalex.org/W2309230723"], "abstract_inverted_index": {"Clustering": [0], "is": [1, 49], "the": [2, 41, 65, 105], "unsupervised": [3], "classification": [4], "of": [5, 40, 67, 81, 94, 108, 115, 131], "patterns": [6], "(observations,": [7], "data": [8, 45], "items,": [9], "or": [10], "feature": [11], "vectors)": [12], "into": [13], "groups": [14], "(clusters).": [15], "The": [16], "clustering": [17, 48, 83, 109, 116, 132], "problem": [18, 52], "has": [19, 63], "been": [20], "addressed": [21], "in": [22, 28, 43, 56, 60], "many": [23, 29], "contexts": [24, 59], "and": [25, 36, 54, 58, 71, 98, 118, 122, 140], "by": [26], "researchers": [27], "disciplines;": [30], "this": [31], "reflects": [32], "its": [33], "broad": [34, 106], "appeal": [35], "usefulness": [37], "as": [38, 135], "one": [39], "steps": [42], "exploratory": [44], "analysis.": [46], "However,": [47], "a": [50, 86, 92, 113], "difficult": [51], "combinatorially,": [53], "differences": [55], "assumptions": [57], "different": [61], "communities": [62], "made": [64], "transfer": [66], "useful": [68, 96], "generic": [69], "concepts": [70, 102], "methodologies": [72], "slow": [73], "to": [74, 100, 104], "occur.": [75], "This": [76], "paper": [77], "presents": [78], "an": [79], "overview": [80], "pattern": [82, 88], "methods": [84], "from": [85], "statistical": [87], "recognition": [89], "perspective,": [90], "with": [91], "goal": [93], "providing": [95], "advice": [97], "references": [99], "fundamental": [101], "accessible": [103], "community": [107], "practitioners.": [110], "We": [111, 125], "present": [112], "taxonomy": [114], "techniques,": [117], "identify": [119], "cross-cutting": [120], "themes": [121], "recent": [123], "advances.": [124], "also": [126], "describe": [127], "some": [128], "important": [129], "applications": [130], "algorithms": [133], "such": [134], "image": [136], "segmentation,": [137], "object": [138], "recognition,": [139], "information": [141], "retrieval.": [142]}, "counts_by_year": [{"year": 2026, "cited_by_count": 203}, {"year": 2025, "cited_by_count": 354}, {"year": 2024, "cited_by_count": 352}, {"year": 2023, "cited_by_count": 368}, {"year": 2022, "cited_by_count": 398}, {"year": 2021, "cited_by_count": 521}, {"year": 2020, "cited_by_count": 538}, {"year": 2019, "cited_by_count": 591}, {"year": 2018, "cited_by_count": 634}, {"year": 2017, "cited_by_count": 649}, {"year": 2016, "cited_by_count": 690}, {"year": 2015, "cited_by_count": 671}, {"year": 2014, "cited_by_count": 762}, {"year": 2013, "cited_by_count": 774}, {"year": 2012, "cited_by_count": 771}], "updated_date": "2026-08-05T07:39:15.569665", "created_date": "2016-06-24T00:00:00"}, {"id": "https://openalex.org/W2962902328", "doi": "https://doi.org/10.18653/v1/p16-1101", "title": "End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF", "display_name": "End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF", "relevance_score": 819.1686, "publication_year": 2016, "publication_date": "2016-01-01", "ids": {"openalex": "https://openalex.org/W2962902328", "doi": "https://doi.org/10.18653/v1/p16-1101", "mag": "2962902328"}, "language": "en", "primary_location": {"id": "doi:10.18653/v1/p16-1101", "is_oa": true, "landing_page_url": "https://doi.org/10.18653/v1/p16-1101", "pdf_url": "https://www.aclweb.org/anthology/P16-1101.pdf", "source": null, "license": "cc-by", "license_id": "https://openalex.org/licenses/cc-by", "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)", "raw_type": "proceedings-article"}, "type": "conference-paper", "indexed_in": ["crossref"], "open_access": {"is_oa": true, "oa_status": "gold", "oa_url": "https://www.aclweb.org/anthology/P16-1101.pdf", "any_repository_has_fulltext": null}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5078672329", "display_name": "Xuezhe Ma", "orcid": "https://orcid.org/0000-0001-7582-1653"}, "institutions": [{"id": "https://openalex.org/I74973139", "display_name": "Carnegie Mellon University", "ror": "https://ror.org/05x2bcf33", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I74973139"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Xuezhe Ma", "raw_affiliation_strings": ["Language Technologies Institute Carnegie Mellon University Pittsburgh, PA 15213, USA"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Language Technologies Institute Carnegie Mellon University Pittsburgh, PA 15213, USA", "institution_ids": ["https://openalex.org/I74973139"]}]}, {"author_position": "last", "author": {"id": "https://openalex.org/A5060225743", "display_name": "Eduard Hovy", "orcid": "https://orcid.org/0000-0002-3270-7903"}, "institutions": [{"id": "https://openalex.org/I74973139", "display_name": "Carnegie Mellon University", "ror": "https://ror.org/05x2bcf33", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I74973139"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Eduard Hovy", "raw_affiliation_strings": ["Language Technologies Institute Carnegie Mellon University Pittsburgh, PA 15213, USA"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Language Technologies Institute Carnegie Mellon University Pittsburgh, PA 15213, USA", "institution_ids": ["https://openalex.org/I74973139"]}]}], "institutions": [], "countries_distinct_count": 1, "institutions_distinct_count": 1, "corresponding_author_ids": [], "corresponding_institution_ids": ["https://openalex.org/I74973139"], "apc_list": null, "apc_paid": null, "fwci": 174.1337, "has_fulltext": true, "cited_by_count": 2595, "citation_normalized_percentile": {"value": 0.99978935, "is_in_top_1_percent": true, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 99, "max": 100}, "biblio": {"volume": null, "issue": null, "first_page": "1064", "last_page": "1074"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 1.0, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 1.0, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9998999834060669, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10201", "display_name": "Speech Recognition and Synthesis", "score": 0.9930999875068665, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.6932210922241211}, {"id": "https://openalex.org/keywords/sequence-labeling", "display_name": "Sequence labeling", "score": 0.632377028465271}, {"id": "https://openalex.org/keywords/end-to-end-principle", "display_name": "End-to-end principle", "score": 0.5836604237556458}, {"id": "https://openalex.org/keywords/sequence", "display_name": "Sequence (biology)", "score": 0.5105618238449097}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.5034558176994324}, {"id": "https://openalex.org/keywords/speech-recognition", "display_name": "Speech recognition", "score": 0.4501124620437622}, {"id": "https://openalex.org/keywords/engineering", "display_name": "Engineering", "score": 0.0935952365398407}, {"id": "https://openalex.org/keywords/chemistry", "display_name": "Chemistry", "score": 0.07217809557914734}], "concepts": [{"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.6932210922241211}, {"id": "https://openalex.org/C35639132", "wikidata": "https://www.wikidata.org/wiki/Q7452468", "display_name": "Sequence labeling", "level": 3, "score": 0.632377028465271}, {"id": "https://openalex.org/C74296488", "wikidata": "https://www.wikidata.org/wiki/Q2527392", "display_name": "End-to-end principle", "level": 2, "score": 0.5836604237556458}, {"id": "https://openalex.org/C2778112365", "wikidata": "https://www.wikidata.org/wiki/Q3511065", "display_name": "Sequence (biology)", "level": 2, "score": 0.5105618238449097}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.5034558176994324}, {"id": "https://openalex.org/C28490314", "wikidata": "https://www.wikidata.org/wiki/Q189436", "display_name": "Speech recognition", "level": 1, "score": 0.4501124620437622}, {"id": "https://openalex.org/C127413603", "wikidata": "https://www.wikidata.org/wiki/Q11023", "display_name": "Engineering", "level": 0, "score": 0.0935952365398407}, {"id": "https://openalex.org/C185592680", "wikidata": "https://www.wikidata.org/wiki/Q2329", "display_name": "Chemistry", "level": 0, "score": 0.07217809557914734}, {"id": "https://openalex.org/C2780451532", "wikidata": "https://www.wikidata.org/wiki/Q759676", "display_name": "Task (project management)", "level": 2, "score": 0.0}, {"id": "https://openalex.org/C55493867", "wikidata": "https://www.wikidata.org/wiki/Q7094", "display_name": "Biochemistry", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C201995342", "wikidata": "https://www.wikidata.org/wiki/Q682496", "display_name": "Systems engineering", "level": 1, "score": 0.0}], "mesh": [], "locations_count": 1, "locations": [{"id": "doi:10.18653/v1/p16-1101", "is_oa": true, "landing_page_url": "https://doi.org/10.18653/v1/p16-1101", "pdf_url": "https://www.aclweb.org/anthology/P16-1101.pdf", "source": null, "license": "cc-by", "license_id": "https://openalex.org/licenses/cc-by", "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)", "raw_type": "proceedings-article"}], "best_oa_location": {"id": "doi:10.18653/v1/p16-1101", "is_oa": true, "landing_page_url": "https://doi.org/10.18653/v1/p16-1101", "pdf_url": "https://www.aclweb.org/anthology/P16-1101.pdf", "source": null, "license": "cc-by", "license_id": "https://openalex.org/licenses/cc-by", "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)", "raw_type": "proceedings-article"}, "sustainable_development_goals": [{"display_name": "Peace, Justice and strong institutions", "score": 0.4099999964237213, "id": "https://metadata.un.org/sdg/16"}], "awards": [{"id": "https://openalex.org/G4713059963", "display_name": null, "funder_award_id": "FA8750", "funder_id": "https://openalex.org/F4320332180", "funder_display_name": "Defense Advanced Research Projects Agency"}, {"id": "https://openalex.org/G5432064702", "display_name": null, "funder_award_id": "FA8750-12-2-0342", "funder_id": "https://openalex.org/F4320332180", "funder_display_name": "Defense Advanced Research Projects Agency"}], "funders": [{"id": "https://openalex.org/F4320332180", "display_name": "Defense Advanced Research Projects Agency", "ror": "https://ror.org/02caytj08"}], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2962902328.pdf", "grobid_xml": "https://content.openalex.org/works/W2962902328.grobid-xml"}, "referenced_works_count": 68, "referenced_works": ["https://openalex.org/W6908809", "https://openalex.org/W581956982", "https://openalex.org/W1515847863", "https://openalex.org/W1522301498", "https://openalex.org/W1533861849", "https://openalex.org/W1570587036", "https://openalex.org/W1632114991", "https://openalex.org/W1677182931", "https://openalex.org/W1815076433", "https://openalex.org/W1899794420", "https://openalex.org/W1940872118", "https://openalex.org/W1951325712", "https://openalex.org/W2004763266", "https://openalex.org/W2008830554", "https://openalex.org/W2045993505", "https://openalex.org/W2056451646", "https://openalex.org/W2064675550", "https://openalex.org/W2095705004", "https://openalex.org/W2096953947", "https://openalex.org/W2101609803", "https://openalex.org/W2104518905", "https://openalex.org/W2107878631", "https://openalex.org/W2108999232", "https://openalex.org/W2111023066", "https://openalex.org/W2114609248", "https://openalex.org/W2116261113", "https://openalex.org/W2116410915", "https://openalex.org/W2119035792", "https://openalex.org/W2130848543", "https://openalex.org/W2130903752", "https://openalex.org/W2134036914", "https://openalex.org/W2136848157", "https://openalex.org/W2137845336", "https://openalex.org/W2139885235", "https://openalex.org/W2143612262", "https://openalex.org/W2144578941", "https://openalex.org/W2147800946", "https://openalex.org/W2147880316", "https://openalex.org/W2153579005", "https://openalex.org/W2156876426", "https://openalex.org/W2158899491", "https://openalex.org/W2168596788", "https://openalex.org/W2170986599", "https://openalex.org/W2249612659", "https://openalex.org/W2250539671", "https://openalex.org/W2250628419", "https://openalex.org/W2250709962", "https://openalex.org/W2250861254", "https://openalex.org/W2251559320", "https://openalex.org/W2251664617", "https://openalex.org/W2251715934", "https://openalex.org/W2296283641", "https://openalex.org/W2299733675", "https://openalex.org/W2308486447", "https://openalex.org/W2399720833", "https://openalex.org/W2949952998", "https://openalex.org/W2952087486", "https://openalex.org/W2952230511", "https://openalex.org/W2963254740", "https://openalex.org/W2963338481", "https://openalex.org/W2963625095", "https://openalex.org/W2963682821", "https://openalex.org/W2963687836", "https://openalex.org/W2964121744", "https://openalex.org/W2964199361", "https://openalex.org/W2964266863", "https://openalex.org/W4285719527", "https://openalex.org/W4294170691"], "related_works": ["https://openalex.org/W3179968364", "https://openalex.org/W2151749779", "https://openalex.org/W1999612375", "https://openalex.org/W2938107654", "https://openalex.org/W3008587939", "https://openalex.org/W3015678144", "https://openalex.org/W2798423868", "https://openalex.org/W4387301579", "https://openalex.org/W2951281592", "https://openalex.org/W3027026357"], "abstract_inverted_index": {"State-of-the-art": [0], "sequence": [1, 68, 81], "labeling": [2, 69, 82], "systems": [3], "traditionally": [4], "require": [5], "large": [6], "amounts": [7], "of": [8, 14, 41, 67], "taskspecific": [9], "knowledge": [10], "in": [11], "the": [12], "form": [13], "handcrafted": [15], "features": [16], "and": [17, 45, 92, 113], "data": [18, 57, 77], "pre-processing.": [19], "In": [20], "this": [21], "paper,": [22], "we": [23], "introduce": [24], "a": [25, 64], "novel": [26], "neutral": [27], "network": [28], "architecture": [29], "that": [30], "benefits": [31], "from": [32], "both": [33, 106], "word-and": [34], "character-level": [35], "representations": [36], "automatically,": [37], "by": [38], "using": [39], "combination": [40], "bidirectional": [42], "LSTM,": [43], "CNN": [44], "CRF.": [46], "Our": [47], "system": [48, 74], "is": [49], "truly": [50], "end-to-end,": [51], "requiring": [52], "no": [53], "feature": [54], "engineering": [55], "or": [56], "preprocessing,": [58], "thus": [59], "making": [60], "it": [61], "applicable": [62], "to": [63], "wide": [65], "range": [66], "tasks.": [70], "We": [71, 101], "evaluate": [72], "our": [73], "on": [75, 105], "two": [76, 80], "sets": [78], "for": [79, 88, 96, 110, 116], "tasks": [83], "-Penn": [84], "Treebank": [85], "WSJ": [86], "corpus": [87, 95], "part-of-speech": [89], "(POS)": [90], "tagging": [91, 112], "CoNLL": [93], "2003": [94], "named": [97], "entity": [98], "recognition": [99], "(NER).": [100], "obtain": [102], "state-of-the-art": [103], "performance": [104], "datasets": [107], "-97.55%": [108], "accuracy": [109], "POS": [111], "91.21%": [114], "F1": [115], "NER.": [117]}, "counts_by_year": [{"year": 2026, "cited_by_count": 37}, {"year": 2025, "cited_by_count": 108}, {"year": 2024, "cited_by_count": 141}, {"year": 2023, "cited_by_count": 260}, {"year": 2022, "cited_by_count": 279}, {"year": 2021, "cited_by_count": 421}, {"year": 2020, "cited_by_count": 451}, {"year": 2019, "cited_by_count": 466}, {"year": 2018, "cited_by_count": 299}, {"year": 2017, "cited_by_count": 104}, {"year": 2016, "cited_by_count": 28}], "updated_date": "2026-07-29T14:22:42.915294", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W2129999749", "doi": "https://doi.org/10.1561/2200000013", "title": "An Introduction to Conditional Random Fields", "display_name": "An Introduction to Conditional Random Fields", "relevance_score": 635.01685, "publication_year": 2012, "publication_date": "2012-01-01", "ids": {"openalex": "https://openalex.org/W2129999749", "doi": "https://doi.org/10.1561/2200000013", "mag": "2129999749"}, "language": "en", "primary_location": {"id": "doi:10.1561/2200000013", "is_oa": false, "landing_page_url": "https://doi.org/10.1561/2200000013", "pdf_url": null, "source": {"id": "https://openalex.org/S4210188176", "display_name": "Foundations and Trends\u00ae in Machine Learning", "issn_l": "1935-8237", "issn": ["1935-8237", "1935-8245"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310318575", "host_organization_name": "Now Publishers", "host_organization_lineage": ["https://openalex.org/P4310318575"], "host_organization_lineage_names": ["Now Publishers"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Foundations and Trends\u00ae in Machine Learning", "raw_type": "journal-article"}, "type": "article", "indexed_in": ["arxiv", "crossref", "datacite"], "open_access": {"is_oa": true, "oa_status": "green", "oa_url": "https://arxiv.org/pdf/1011.4088", "any_repository_has_fulltext": true}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5028501178", "display_name": "Charles Sutton", "orcid": "https://orcid.org/0000-0002-0041-3820"}, "institutions": [{"id": "https://openalex.org/I98677209", "display_name": "University of Edinburgh", "ror": "https://ror.org/01nrxwf90", "country_code": "GB", "type": "education", "lineage": ["https://openalex.org/I98677209"]}], "countries": ["GB"], "is_corresponding": false, "raw_author_name": "Charles Sutton", "raw_affiliation_strings": ["School of Informatics, University of Edinburgh , Edinburgh, EH8 9AB,", "Sch. of Informatics, Univ. of Edinburgh, UK"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "School of Informatics, University of Edinburgh , Edinburgh, EH8 9AB,", "institution_ids": ["https://openalex.org/I98677209"]}, {"raw_affiliation_string": "Sch. of Informatics, Univ. of Edinburgh, UK", "institution_ids": ["https://openalex.org/I98677209"]}]}, {"author_position": "last", "author": {"id": "https://openalex.org/A5107835063", "display_name": "Andrew McCallum", "orcid": null}, "institutions": [{"id": "https://openalex.org/I24603500", "display_name": "University of Massachusetts Amherst", "ror": "https://ror.org/0072zz521", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I24603500"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Andrew McCallum", "raw_affiliation_strings": ["Department of Computer Science, University of Massachusetts , Amherst, , 01003,", "Department of Computer Science, University of Massachusetts, USA#TAB#"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Department of Computer Science, University of Massachusetts , Amherst, , 01003,", "institution_ids": ["https://openalex.org/I24603500"]}, {"raw_affiliation_string": "Department of Computer Science, University of Massachusetts, USA#TAB#", "institution_ids": ["https://openalex.org/I24603500"]}]}], "institutions": [], "countries_distinct_count": 2, "institutions_distinct_count": 2, "corresponding_author_ids": [], "corresponding_institution_ids": [], "apc_list": null, "apc_paid": null, "fwci": 61.4158, "has_fulltext": true, "cited_by_count": 529, "citation_normalized_percentile": {"value": 0.99919119, "is_in_top_1_percent": true, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 90, "max": 100}, "biblio": {"volume": "4", "issue": "4", "first_page": "267", "last_page": "373"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T12535", "display_name": "Machine Learning and Data Classification", "score": 0.9980000257492065, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T12535", "display_name": "Machine Learning and Data Classification", "score": 0.9980000257492065, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T11303", "display_name": "Bayesian Modeling and Causal Inference", "score": 0.9973000288009644, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10320", "display_name": "Neural Networks and Applications", "score": 0.9909999966621399, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/crfs", "display_name": "CRFS", "score": 0.9806188344955444}, {"id": "https://openalex.org/keywords/conditional-random-field", "display_name": "Conditional random field", "score": 0.9087752103805542}, {"id": "https://openalex.org/keywords/graphical-model", "display_name": "Graphical model", "score": 0.9032363891601562}, {"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.7001571655273438}, {"id": "https://openalex.org/keywords/inference", "display_name": "Inference", "score": 0.5923212170600891}, {"id": "https://openalex.org/keywords/data-mining", "display_name": "Data mining", "score": 0.5397940278053284}, {"id": "https://openalex.org/keywords/machine-learning", "display_name": "Machine learning", "score": 0.5192394256591797}, {"id": "https://openalex.org/keywords/probabilistic-logic", "display_name": "Probabilistic logic", "score": 0.5009329319000244}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.49462220072746277}, {"id": "https://openalex.org/keywords/bayesian-network", "display_name": "Bayesian network", "score": 0.4880894422531128}, {"id": "https://openalex.org/keywords/multivariate-statistics", "display_name": "Multivariate statistics", "score": 0.4597914218902588}, {"id": "https://openalex.org/keywords/probabilistic-classification", "display_name": "Probabilistic classification", "score": 0.4562701880931854}, {"id": "https://openalex.org/keywords/field", "display_name": "Field (mathematics)", "score": 0.438317209482193}, {"id": "https://openalex.org/keywords/variety", "display_name": "Variety (cybernetics)", "score": 0.4246058464050293}, {"id": "https://openalex.org/keywords/naive-bayes-classifier", "display_name": "Naive Bayes classifier", "score": 0.23462098836898804}, {"id": "https://openalex.org/keywords/support-vector-machine", "display_name": "Support vector machine", "score": 0.17999699711799622}, {"id": "https://openalex.org/keywords/mathematics", "display_name": "Mathematics", "score": 0.1447882056236267}], "concepts": [{"id": "https://openalex.org/C2775953691", "wikidata": "https://www.wikidata.org/wiki/Q5013874", "display_name": "CRFS", "level": 3, "score": 0.9806188344955444}, {"id": "https://openalex.org/C152565575", "wikidata": "https://www.wikidata.org/wiki/Q1124538", "display_name": "Conditional random field", "level": 2, "score": 0.9087752103805542}, {"id": "https://openalex.org/C155846161", "wikidata": "https://www.wikidata.org/wiki/Q1143367", "display_name": "Graphical model", "level": 2, "score": 0.9032363891601562}, {"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.7001571655273438}, {"id": "https://openalex.org/C2776214188", "wikidata": "https://www.wikidata.org/wiki/Q408386", "display_name": "Inference", "level": 2, "score": 0.5923212170600891}, {"id": "https://openalex.org/C124101348", "wikidata": "https://www.wikidata.org/wiki/Q172491", "display_name": "Data mining", "level": 1, "score": 0.5397940278053284}, {"id": "https://openalex.org/C119857082", "wikidata": "https://www.wikidata.org/wiki/Q2539", "display_name": "Machine learning", "level": 1, "score": 0.5192394256591797}, {"id": "https://openalex.org/C49937458", "wikidata": "https://www.wikidata.org/wiki/Q2599292", "display_name": "Probabilistic logic", "level": 2, "score": 0.5009329319000244}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.49462220072746277}, {"id": "https://openalex.org/C33724603", "wikidata": "https://www.wikidata.org/wiki/Q812540", "display_name": "Bayesian network", "level": 2, "score": 0.4880894422531128}, {"id": "https://openalex.org/C161584116", "wikidata": "https://www.wikidata.org/wiki/Q1952580", "display_name": "Multivariate statistics", "level": 2, "score": 0.4597914218902588}, {"id": "https://openalex.org/C189119545", "wikidata": "https://www.wikidata.org/wiki/Q5128022", "display_name": "Probabilistic classification", "level": 4, "score": 0.4562701880931854}, {"id": "https://openalex.org/C9652623", "wikidata": "https://www.wikidata.org/wiki/Q190109", "display_name": "Field (mathematics)", "level": 2, "score": 0.438317209482193}, {"id": "https://openalex.org/C136197465", "wikidata": "https://www.wikidata.org/wiki/Q1729295", "display_name": "Variety (cybernetics)", "level": 2, "score": 0.4246058464050293}, {"id": "https://openalex.org/C52001869", "wikidata": "https://www.wikidata.org/wiki/Q812530", "display_name": "Naive Bayes classifier", "level": 3, "score": 0.23462098836898804}, {"id": "https://openalex.org/C12267149", "wikidata": "https://www.wikidata.org/wiki/Q282453", "display_name": "Support vector machine", "level": 2, "score": 0.17999699711799622}, {"id": "https://openalex.org/C33923547", "wikidata": "https://www.wikidata.org/wiki/Q395", "display_name": "Mathematics", "level": 0, "score": 0.1447882056236267}, {"id": "https://openalex.org/C202444582", "wikidata": "https://www.wikidata.org/wiki/Q837863", "display_name": "Pure mathematics", "level": 1, "score": 0.0}], "mesh": [], "locations_count": 9, "locations": [{"id": "doi:10.1561/2200000013", "is_oa": false, "landing_page_url": "https://doi.org/10.1561/2200000013", "pdf_url": null, "source": {"id": "https://openalex.org/S4210188176", "display_name": "Foundations and Trends\u00ae in Machine Learning", "issn_l": "1935-8237", "issn": ["1935-8237", "1935-8245"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310318575", "host_organization_name": "Now Publishers", "host_organization_lineage": ["https://openalex.org/P4310318575"], "host_organization_lineage_names": ["Now Publishers"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Foundations and Trends\u00ae in Machine Learning", "raw_type": "journal-article"}, {"id": "doi:10.1561/9781601985736", "is_oa": false, "landing_page_url": "https://doi.org/10.1561/9781601985736", "pdf_url": null, "source": {"id": "https://openalex.org/S4306463678", "display_name": "now publishers, Inc. eBooks", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": null, "host_organization_name": null, "host_organization_lineage": [], "host_organization_lineage_names": [], "type": "ebook platform"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": null, "raw_type": "monograph"}, {"id": "pmh:oai:arXiv.org:1011.4088", "is_oa": true, "landing_page_url": "http://arxiv.org/abs/1011.4088", "pdf_url": "https://arxiv.org/pdf/1011.4088", "source": {"id": "https://openalex.org/S4306400194", "display_name": "arXiv (Cornell University)", "issn_l": "2331-8422", "issn": ["2331-8422"], "is_oa": true, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I205783295", "host_organization_name": "Cornell University", "host_organization_lineage": ["https://openalex.org/I205783295"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "", "raw_type": "text"}, {"id": "pmh:oai:pure.ed.ac.uk:publications/a370c672-8246-4aba-a55d-25544992dac2", "is_oa": true, "landing_page_url": "https://www.research.ed.ac.uk/en/publications/a370c672-8246-4aba-a55d-25544992dac2", "pdf_url": "https://www.pure.ed.ac.uk/ws/files/10482724/crftut_fnt.pdf", "source": {"id": "https://openalex.org/S4306400321", "display_name": "Edinburgh Research Explorer (University of Edinburgh)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I98677209", "host_organization_name": "University of Edinburgh", "host_organization_lineage": ["https://openalex.org/I98677209"], "host_organization_lineage_names": [], "type": "repository"}, "license": "other-oa", "license_id": "https://openalex.org/licenses/other-oa", "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Sutton, C & McCallum, A 2012, 'An Introduction to Conditional Random Fields', Foundations and Trends in Machine Learning, vol. 4, no. 4, pp. 267-373. https://doi.org/10.1561/2200000013", "raw_type": "info:eu-repo/semantics/article"}, {"id": "mag:2950342388", "is_oa": true, "landing_page_url": "https://arxiv.org/pdf/1011.4088v1", "pdf_url": null, "source": {"id": "https://openalex.org/S4306400194", "display_name": "arXiv (Cornell University)", "issn_l": "2331-8422", "issn": ["2331-8422"], "is_oa": true, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I205783295", "host_organization_name": "Cornell University", "host_organization_lineage": ["https://openalex.org/I205783295"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "arXiv (Cornell University)", "raw_type": null}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.259.5050", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.259.5050", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cs.umass.edu/%7Ecasutton/publications/crftut-fnt.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.754.9686", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.754.9686", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://arxiv.org/pdf/1011.4088.pdf", "raw_type": "text"}, {"id": "pmh:oai:pure.ed.ac.uk:openaire/a370c672-8246-4aba-a55d-25544992dac2", "is_oa": true, "landing_page_url": "https://hdl.handle.net/20.500.11820/a370c672-8246-4aba-a55d-25544992dac2", "pdf_url": null, "source": {"id": "https://openalex.org/S4306400321", "display_name": "Edinburgh Research Explorer (University of Edinburgh)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I98677209", "host_organization_name": "University of Edinburgh", "host_organization_lineage": ["https://openalex.org/I98677209"], "host_organization_lineage_names": [], "type": "repository"}, "license": "other-oa", "license_id": "https://openalex.org/licenses/other-oa", "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Sutton, C & McCallum, A 2012, 'An Introduction to Conditional Random Fields', Foundations and Trends in Machine Learning, vol. 4, no. 4, pp. 267-373. https://doi.org/10.1561/2200000013", "raw_type": "info:eu-repo/semantics/article"}, {"id": "doi:10.48550/arxiv.1011.4088", "is_oa": true, "landing_page_url": "https://doi.org/10.48550/arxiv.1011.4088", "pdf_url": null, "source": {"id": "https://openalex.org/S4306400194", "display_name": "arXiv (Cornell University)", "issn_l": "2331-8422", "issn": ["2331-8422"], "is_oa": true, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I205783295", "host_organization_name": "Cornell University", "host_organization_lineage": ["https://openalex.org/I205783295"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": null, "is_accepted": false, "is_published": null, "raw_source_name": null, "raw_type": "Preprint"}], "best_oa_location": {"id": "pmh:oai:arXiv.org:1011.4088", "is_oa": true, "landing_page_url": "http://arxiv.org/abs/1011.4088", "pdf_url": "https://arxiv.org/pdf/1011.4088", "source": {"id": "https://openalex.org/S4306400194", "display_name": "arXiv (Cornell University)", "issn_l": "2331-8422", "issn": ["2331-8422"], "is_oa": true, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I205783295", "host_organization_name": "Cornell University", "host_organization_lineage": ["https://openalex.org/I205783295"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "", "raw_type": "text"}, "sustainable_development_goals": [{"display_name": "Quality Education", "score": 0.7799999713897705, "id": "https://metadata.un.org/sdg/4"}], "awards": [], "funders": [], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2129999749.pdf", "grobid_xml": "https://content.openalex.org/works/W2129999749.grobid-xml"}, "referenced_works_count": 164, "referenced_works": ["https://openalex.org/W1176919", "https://openalex.org/W28766783", "https://openalex.org/W35586085", "https://openalex.org/W47392883", "https://openalex.org/W80430187", "https://openalex.org/W86146351", "https://openalex.org/W130710483", "https://openalex.org/W130850236", "https://openalex.org/W147273232", "https://openalex.org/W160370694", "https://openalex.org/W165283731", "https://openalex.org/W173906397", "https://openalex.org/W1511867968", "https://openalex.org/W1511986666", "https://openalex.org/W1515020792", "https://openalex.org/W1517555081", "https://openalex.org/W1525888637", "https://openalex.org/W1526729636", "https://openalex.org/W1528789833", "https://openalex.org/W1528797350", "https://openalex.org/W1530235965", "https://openalex.org/W1533758202", "https://openalex.org/W1534730506", "https://openalex.org/W1542491098", "https://openalex.org/W1563520220", "https://openalex.org/W1632114991", "https://openalex.org/W1651266332", "https://openalex.org/W1714704734", "https://openalex.org/W1766290689", "https://openalex.org/W1775188621", "https://openalex.org/W1842236176", "https://openalex.org/W1857926807", "https://openalex.org/W1877570817", "https://openalex.org/W1880262756", "https://openalex.org/W1909733559", "https://openalex.org/W1934019294", "https://openalex.org/W1947685456", "https://openalex.org/W1952794764", "https://openalex.org/W1964803612", "https://openalex.org/W1971288000", "https://openalex.org/W1972950354", "https://openalex.org/W1977970897", "https://openalex.org/W1980925709", "https://openalex.org/W1983599491", "https://openalex.org/W1985093013", "https://openalex.org/W1986916218", "https://openalex.org/W1994616650", "https://openalex.org/W1996430422", "https://openalex.org/W1998839399", "https://openalex.org/W2004915807", "https://openalex.org/W2008652694", "https://openalex.org/W2009797711", "https://openalex.org/W2010624529", "https://openalex.org/W2020999234", "https://openalex.org/W2026129786", "https://openalex.org/W2034797903", "https://openalex.org/W2036102925", "https://openalex.org/W2036516910", "https://openalex.org/W2041522124", "https://openalex.org/W2047782770", "https://openalex.org/W2048500237", "https://openalex.org/W2058839679", "https://openalex.org/W2075635421", "https://openalex.org/W2083875149", "https://openalex.org/W2086240273", "https://openalex.org/W2095844239", "https://openalex.org/W2096071754", "https://openalex.org/W2096765155", "https://openalex.org/W2098921539", "https://openalex.org/W2099396914", "https://openalex.org/W2099960657", "https://openalex.org/W2101534792", "https://openalex.org/W2101913237", "https://openalex.org/W2102294561", "https://openalex.org/W2102667697", "https://openalex.org/W2104029044", "https://openalex.org/W2105644991", "https://openalex.org/W2107188136", "https://openalex.org/W2109189215", "https://openalex.org/W2109722477", "https://openalex.org/W2112796928", "https://openalex.org/W2114220616", "https://openalex.org/W2114521167", "https://openalex.org/W2114860583", "https://openalex.org/W2116064496", "https://openalex.org/W2116877738", "https://openalex.org/W2119224513", "https://openalex.org/W2120340025", "https://openalex.org/W2122853437", "https://openalex.org/W2124351162", "https://openalex.org/W2124386111", "https://openalex.org/W2125838338", "https://openalex.org/W2125993116", "https://openalex.org/W2126276057", "https://openalex.org/W2127686544", "https://openalex.org/W2129031807", "https://openalex.org/W2129191766", "https://openalex.org/W2129712609", "https://openalex.org/W2133233009", "https://openalex.org/W2133236963", "https://openalex.org/W2134134392", "https://openalex.org/W2134275125", "https://openalex.org/W2134827050", "https://openalex.org/W2136064009", "https://openalex.org/W2136140395", "https://openalex.org/W2137813581", "https://openalex.org/W2139193890", "https://openalex.org/W2139686264", "https://openalex.org/W2141099517", "https://openalex.org/W2141732516", "https://openalex.org/W2142276227", "https://openalex.org/W2142500366", "https://openalex.org/W2142623206", "https://openalex.org/W2143458716", "https://openalex.org/W2144578941", "https://openalex.org/W2145494108", "https://openalex.org/W2147196093", "https://openalex.org/W2147880316", "https://openalex.org/W2149660837", "https://openalex.org/W2150969560", "https://openalex.org/W2151322733", "https://openalex.org/W2152455533", "https://openalex.org/W2152463966", "https://openalex.org/W2152540201", "https://openalex.org/W2154368244", "https://openalex.org/W2156346614", "https://openalex.org/W2156515921", "https://openalex.org/W2156615793", "https://openalex.org/W2157171712", "https://openalex.org/W2157711174", "https://openalex.org/W2158188757", "https://openalex.org/W2158349948", "https://openalex.org/W2158823144", "https://openalex.org/W2159080219", "https://openalex.org/W2159992248", "https://openalex.org/W2160218441", "https://openalex.org/W2160986985", "https://openalex.org/W2160988325", "https://openalex.org/W2161914416", "https://openalex.org/W2163191289", "https://openalex.org/W2163614729", "https://openalex.org/W2168356304", "https://openalex.org/W2168820925", "https://openalex.org/W2169336678", "https://openalex.org/W2169415915", "https://openalex.org/W2169498096", "https://openalex.org/W2169551590", "https://openalex.org/W2169918010", "https://openalex.org/W2170694982", "https://openalex.org/W2170979168", "https://openalex.org/W2186534467", "https://openalex.org/W2429914308", "https://openalex.org/W2552605897", "https://openalex.org/W2798766386", "https://openalex.org/W2914484425", "https://openalex.org/W2914746235", "https://openalex.org/W2949198759", "https://openalex.org/W2951085448", "https://openalex.org/W2962735828", "https://openalex.org/W2963059527", "https://openalex.org/W2994982620", "https://openalex.org/W3029645440", "https://openalex.org/W3100265218", "https://openalex.org/W3140968660"], "related_works": ["https://openalex.org/W2147880316", "https://openalex.org/W2064675550", "https://openalex.org/W2125838338", "https://openalex.org/W2296283641", "https://openalex.org/W2250539671", "https://openalex.org/W1511986666", "https://openalex.org/W2156515921", "https://openalex.org/W2020278455", "https://openalex.org/W2964121744", "https://openalex.org/W2141099517", "https://openalex.org/W1766290689", "https://openalex.org/W1663973292", "https://openalex.org/W2144578941", "https://openalex.org/W2051434435", "https://openalex.org/W1940872118", "https://openalex.org/W1934019294", "https://openalex.org/W2159080219", "https://openalex.org/W2096765155", "https://openalex.org/W2120340025", "https://openalex.org/W2123442489"], "abstract_inverted_index": {"An": [0], "Introduction": [1], "to": [2, 15, 32, 35], "Conditional": [3], "Random": [4], "Fields": [5], "provides": [6], "a": [7, 38], "comprehensive": [8], "tutorial": [9], "aimed": [10], "at": [11], "application-oriented": [12], "practitioners": [13, 36], "seeking": [14], "apply": [16], "CRFs.": [17], "The": [18], "monograph": [19], "does": [20], "not": [21], "assume": [22], "previous": [23], "knowledge": [24], "of": [25, 41], "graphical": [26], "modeling,": [27], "and": [28], "so": [29], "is": [30], "intended": [31], "be": [33], "useful": [34], "in": [37], "wide": [39], "variety": [40], "fields.": [42]}, "counts_by_year": [{"year": 2025, "cited_by_count": 2}, {"year": 2024, "cited_by_count": 1}, {"year": 2023, "cited_by_count": 2}, {"year": 2022, "cited_by_count": 5}, {"year": 2021, "cited_by_count": 49}, {"year": 2020, "cited_by_count": 73}, {"year": 2019, "cited_by_count": 67}, {"year": 2018, "cited_by_count": 69}, {"year": 2017, "cited_by_count": 56}, {"year": 2016, "cited_by_count": 61}, {"year": 2015, "cited_by_count": 46}, {"year": 2014, "cited_by_count": 42}, {"year": 2013, "cited_by_count": 29}, {"year": 2012, "cited_by_count": 17}], "updated_date": "2026-07-28T07:46:37.118299", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W2171671120", "doi": "https://doi.org/10.3115/1613715.1613855", "title": "An analysis of active learning strategies for sequence labeling tasks", "display_name": "An analysis of active learning strategies for sequence labeling tasks", "relevance_score": 591.2018, "publication_year": 2008, "publication_date": "2008-01-01", "ids": {"openalex": "https://openalex.org/W2171671120", "doi": "https://doi.org/10.3115/1613715.1613855", "mag": "2171671120"}, "language": "en", "primary_location": {"id": "doi:10.3115/1613715.1613855", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1613715.1613855", "pdf_url": "https://dl.acm.org/doi/pdf/10.5555/1613715.1613855", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the Conference on Empirical Methods in Natural Language Processing - EMNLP '08", "raw_type": "proceedings-article"}, "type": "conference-abstract", "indexed_in": ["crossref"], "open_access": {"is_oa": true, "oa_status": "gold", "oa_url": "https://dl.acm.org/doi/pdf/10.5555/1613715.1613855", "any_repository_has_fulltext": null}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5028683722", "display_name": "Burr Settles", "orcid": null}, "institutions": [{"id": "https://openalex.org/I135310074", "display_name": "University of Wisconsin\u2013Madison", "ror": "https://ror.org/01y2jtd41", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I135310074"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Burr Settles", "raw_affiliation_strings": ["University of Wisconsin, Madison, WI"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Wisconsin, Madison, WI", "institution_ids": ["https://openalex.org/I135310074"]}]}, {"author_position": "last", "author": {"id": "https://openalex.org/A5071722704", "display_name": "Mark Craven", "orcid": "https://orcid.org/0000-0002-8917-7464"}, "institutions": [{"id": "https://openalex.org/I135310074", "display_name": "University of Wisconsin\u2013Madison", "ror": "https://ror.org/01y2jtd41", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I135310074"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Mark Craven", "raw_affiliation_strings": ["University of Wisconsin, Madison, WI"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Wisconsin, Madison, WI", "institution_ids": ["https://openalex.org/I135310074"]}]}], "institutions": [], "countries_distinct_count": 1, "institutions_distinct_count": 1, "corresponding_author_ids": [], "corresponding_institution_ids": ["https://openalex.org/I135310074"], "apc_list": null, "apc_paid": null, "fwci": null, "has_fulltext": true, "cited_by_count": 995, "citation_normalized_percentile": null, "cited_by_percentile_year": null, "biblio": {"volume": null, "issue": null, "first_page": "1070", "last_page": "1070"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T12072", "display_name": "Machine Learning and Algorithms", "score": 0.9998999834060669, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T12072", "display_name": "Machine Learning and Algorithms", "score": 0.9998999834060669, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 0.9969000220298767, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T11269", "display_name": "Algorithms and Data Compression", "score": 0.9965999722480774, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.8456761837005615}, {"id": "https://openalex.org/keywords/sequence-labeling", "display_name": "Sequence labeling", "score": 0.804955244064331}, {"id": "https://openalex.org/keywords/active-learning", "display_name": "Active learning (machine learning)", "score": 0.6812852621078491}, {"id": "https://openalex.org/keywords/annotation", "display_name": "Annotation", "score": 0.6257632970809937}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.5855444073677063}, {"id": "https://openalex.org/keywords/sequence", "display_name": "Sequence (biology)", "score": 0.5810056924819946}, {"id": "https://openalex.org/keywords/machine-learning", "display_name": "Machine learning", "score": 0.5248817801475525}, {"id": "https://openalex.org/keywords/information-extraction", "display_name": "Information extraction", "score": 0.5219513773918152}, {"id": "https://openalex.org/keywords/selection", "display_name": "Selection (genetic algorithm)", "score": 0.47516223788261414}, {"id": "https://openalex.org/keywords/segmentation", "display_name": "Segmentation", "score": 0.45882439613342285}, {"id": "https://openalex.org/keywords/sequence-learning", "display_name": "Sequence learning", "score": 0.4123448133468628}, {"id": "https://openalex.org/keywords/natural-language-processing", "display_name": "Natural language processing", "score": 0.3342124819755554}, {"id": "https://openalex.org/keywords/task", "display_name": "Task (project management)", "score": 0.2254069447517395}], "concepts": [{"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.8456761837005615}, {"id": "https://openalex.org/C35639132", "wikidata": "https://www.wikidata.org/wiki/Q7452468", "display_name": "Sequence labeling", "level": 3, "score": 0.804955244064331}, {"id": "https://openalex.org/C77967617", "wikidata": "https://www.wikidata.org/wiki/Q4677561", "display_name": "Active learning (machine learning)", "level": 2, "score": 0.6812852621078491}, {"id": "https://openalex.org/C2776321320", "wikidata": "https://www.wikidata.org/wiki/Q857525", "display_name": "Annotation", "level": 2, "score": 0.6257632970809937}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.5855444073677063}, {"id": "https://openalex.org/C2778112365", "wikidata": "https://www.wikidata.org/wiki/Q3511065", "display_name": "Sequence (biology)", "level": 2, "score": 0.5810056924819946}, {"id": "https://openalex.org/C119857082", "wikidata": "https://www.wikidata.org/wiki/Q2539", "display_name": "Machine learning", "level": 1, "score": 0.5248817801475525}, {"id": "https://openalex.org/C195807954", "wikidata": "https://www.wikidata.org/wiki/Q1662562", "display_name": "Information extraction", "level": 2, "score": 0.5219513773918152}, {"id": "https://openalex.org/C81917197", "wikidata": "https://www.wikidata.org/wiki/Q628760", "display_name": "Selection (genetic algorithm)", "level": 2, "score": 0.47516223788261414}, {"id": "https://openalex.org/C89600930", "wikidata": "https://www.wikidata.org/wiki/Q1423946", "display_name": "Segmentation", "level": 2, "score": 0.45882439613342285}, {"id": "https://openalex.org/C40506919", "wikidata": "https://www.wikidata.org/wiki/Q7452469", "display_name": "Sequence learning", "level": 2, "score": 0.4123448133468628}, {"id": "https://openalex.org/C204321447", "wikidata": "https://www.wikidata.org/wiki/Q30642", "display_name": "Natural language processing", "level": 1, "score": 0.3342124819755554}, {"id": "https://openalex.org/C2780451532", "wikidata": "https://www.wikidata.org/wiki/Q759676", "display_name": "Task (project management)", "level": 2, "score": 0.2254069447517395}, {"id": "https://openalex.org/C187736073", "wikidata": "https://www.wikidata.org/wiki/Q2920921", "display_name": "Management", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C54355233", "wikidata": "https://www.wikidata.org/wiki/Q7162", "display_name": "Genetics", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C86803240", "wikidata": "https://www.wikidata.org/wiki/Q420", "display_name": "Biology", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C162324750", "wikidata": "https://www.wikidata.org/wiki/Q8134", "display_name": "Economics", "level": 0, "score": 0.0}], "mesh": [], "locations_count": 3, "locations": [{"id": "doi:10.3115/1613715.1613855", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1613715.1613855", "pdf_url": "https://dl.acm.org/doi/pdf/10.5555/1613715.1613855", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the Conference on Empirical Methods in Natural Language Processing - EMNLP '08", "raw_type": "proceedings-article"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.139.6640", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.139.6640", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.biostat.wisc.edu/~craven/papers/settles.emnlp08.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.187.7401", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.187.7401", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.aclweb.org/anthology-new/D/D08/D08-1112.pdf", "raw_type": "text"}], "best_oa_location": {"id": "doi:10.3115/1613715.1613855", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1613715.1613855", "pdf_url": "https://dl.acm.org/doi/pdf/10.5555/1613715.1613855", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the Conference on Empirical Methods in Natural Language Processing - EMNLP '08", "raw_type": "proceedings-article"}, "sustainable_development_goals": [{"display_name": "Quality Education", "score": 0.8299999833106995, "id": "https://metadata.un.org/sdg/4"}], "awards": [], "funders": [{"id": "https://openalex.org/F4320332161", "display_name": "National Institutes of Health", "ror": "https://ror.org/01cwqze88"}], "has_content": {"grobid_xml": false, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2171671120.pdf"}, "referenced_works_count": 36, "referenced_works": ["https://openalex.org/W153277182", "https://openalex.org/W163605501", "https://openalex.org/W1484084878", "https://openalex.org/W1513874326", "https://openalex.org/W1514707997", "https://openalex.org/W1524975733", "https://openalex.org/W1534730506", "https://openalex.org/W1549011711", "https://openalex.org/W1553262910", "https://openalex.org/W1580375566", "https://openalex.org/W1623072288", "https://openalex.org/W1766290689", "https://openalex.org/W1969887143", "https://openalex.org/W1978470410", "https://openalex.org/W1995875735", "https://openalex.org/W2010588484", "https://openalex.org/W2018770010", "https://openalex.org/W2018874418", "https://openalex.org/W2047782770", "https://openalex.org/W2080021732", "https://openalex.org/W2113152670", "https://openalex.org/W2117763124", "https://openalex.org/W2125838338", "https://openalex.org/W2127816222", "https://openalex.org/W2128678390", "https://openalex.org/W2144578941", "https://openalex.org/W2147880316", "https://openalex.org/W2151023586", "https://openalex.org/W2162401759", "https://openalex.org/W2951562155", "https://openalex.org/W2952087486", "https://openalex.org/W2993383518", "https://openalex.org/W3171280080", "https://openalex.org/W4230030242", "https://openalex.org/W4245826738", "https://openalex.org/W4253573210"], "related_works": ["https://openalex.org/W2361861616", "https://openalex.org/W2263699433", "https://openalex.org/W2377979023", "https://openalex.org/W2218034408", "https://openalex.org/W4298158270", "https://openalex.org/W2271496879", "https://openalex.org/W2996274640", "https://openalex.org/W156512209", "https://openalex.org/W4226172942", "https://openalex.org/W4323520198"], "abstract_inverted_index": {"Active": [0], "learning": [1, 33], "is": [2, 19], "well-suited": [3], "to": [4, 26, 61], "many": [5], "problems": [6], "in": [7], "natural": [8], "language": [9], "processing,": [10], "where": [11], "unlabeled": [12], "data": [13], "may": [14], "be": [15], "abundant": [16], "but": [17], "annotation": [18], "slow": [20], "and": [21, 43, 56], "expensive.": [22], "This": [23], "paper": [24], "aims": [25], "shed": [27], "light": [28], "on": [29], "the": [30, 82, 85], "best": [31], "active": [32], "approaches": [34], "for": [35, 53], "sequence": [36, 54], "labeling": [37], "tasks": [38], "such": [39], "as": [40], "information": [41], "extraction": [42], "document": [44], "segmentation.": [45], "We": [46, 65], "survey": [47], "previously": [48], "used": [49], "query": [50], "selection": [51], "strategies": [52], "models,": [55], "propose": [57], "several": [58], "novel": [59], "algorithms": [60], "address": [62], "their": [63], "shortcomings.": [64], "also": [66], "conduct": [67], "a": [68], "large-scale": [69], "empirical": [70], "comparison": [71], "using": [72], "multiple": [73], "corpora,": [74], "which": [75], "demonstrates": [76], "that": [77], "our": [78], "proposed": [79], "methods": [80], "advance": [81], "state": [83], "of": [84], "art.": [86]}, "counts_by_year": [{"year": 2026, "cited_by_count": 15}, {"year": 2025, "cited_by_count": 34}, {"year": 2024, "cited_by_count": 59}, {"year": 2023, "cited_by_count": 76}, {"year": 2022, "cited_by_count": 78}, {"year": 2021, "cited_by_count": 111}, {"year": 2020, "cited_by_count": 103}, {"year": 2019, "cited_by_count": 69}, {"year": 2018, "cited_by_count": 86}, {"year": 2017, "cited_by_count": 70}, {"year": 2016, "cited_by_count": 46}, {"year": 2015, "cited_by_count": 50}, {"year": 2014, "cited_by_count": 51}, {"year": 2013, "cited_by_count": 45}, {"year": 2012, "cited_by_count": 39}], "updated_date": "2026-08-04T08:18:43.703281", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W2036516910", "doi": "https://doi.org/10.3115/1220355.1220436", "title": "Chinese segmentation and new word detection using conditional random fields", "display_name": "Chinese segmentation and new word detection using conditional random fields", "relevance_score": 572.0986, "publication_year": 2004, "publication_date": "2004-01-01", "ids": {"openalex": "https://openalex.org/W2036516910", "doi": "https://doi.org/10.3115/1220355.1220436", "mag": "2036516910"}, "language": "en", "primary_location": {"id": "doi:10.3115/1220355.1220436", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1220355.1220436", "pdf_url": "https://dl.acm.org/doi/pdf/10.3115/1220355.1220436", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the 20th international conference on Computational Linguistics - COLING '04", "raw_type": "proceedings-article"}, "type": "conference-paper", "indexed_in": ["crossref"], "open_access": {"is_oa": true, "oa_status": "gold", "oa_url": "https://dl.acm.org/doi/pdf/10.3115/1220355.1220436", "any_repository_has_fulltext": null}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5047400593", "display_name": "Fuchun Peng", "orcid": null}, "institutions": [{"id": "https://openalex.org/I24603500", "display_name": "University of Massachusetts Amherst", "ror": "https://ror.org/0072zz521", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I24603500"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Fuchun Peng", "raw_affiliation_strings": ["University of Massachusetts Amherst, Amherst, MA", "University of Massachusetts Amherst Amherst, MA"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Massachusetts Amherst, Amherst, MA", "institution_ids": ["https://openalex.org/I24603500"]}, {"raw_affiliation_string": "University of Massachusetts Amherst Amherst, MA", "institution_ids": ["https://openalex.org/I24603500"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5103468848", "display_name": "Fangfang Feng", "orcid": null}, "institutions": [{"id": "https://openalex.org/I24603500", "display_name": "University of Massachusetts Amherst", "ror": "https://ror.org/0072zz521", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I24603500"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Fangfang Feng", "raw_affiliation_strings": ["University of Massachusetts Amherst, Amherst, MA", "University of Massachusetts Amherst Amherst, MA"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Massachusetts Amherst, Amherst, MA", "institution_ids": ["https://openalex.org/I24603500"]}, {"raw_affiliation_string": "University of Massachusetts Amherst Amherst, MA", "institution_ids": ["https://openalex.org/I24603500"]}]}, {"author_position": "last", "author": {"id": "https://openalex.org/A5107835063", "display_name": "Andrew McCallum", "orcid": null}, "institutions": [{"id": "https://openalex.org/I24603500", "display_name": "University of Massachusetts Amherst", "ror": "https://ror.org/0072zz521", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I24603500"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Andrew McCallum", "raw_affiliation_strings": ["University of Massachusetts Amherst, Amherst, MA", "University of Massachusetts Amherst Amherst, MA"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Massachusetts Amherst, Amherst, MA", "institution_ids": ["https://openalex.org/I24603500"]}, {"raw_affiliation_string": "University of Massachusetts Amherst Amherst, MA", "institution_ids": ["https://openalex.org/I24603500"]}]}], "institutions": [], "countries_distinct_count": 1, "institutions_distinct_count": 1, "corresponding_author_ids": [], "corresponding_institution_ids": ["https://openalex.org/I24603500"], "apc_list": null, "apc_paid": null, "fwci": 9.2622, "has_fulltext": true, "cited_by_count": 468, "citation_normalized_percentile": {"value": 0.9861502, "is_in_top_1_percent": false, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 97, "max": 100}, "biblio": {"volume": null, "issue": null, "first_page": "562", "last_page": "es"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 0.9998999834060669, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 0.9998999834060669, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9998000264167786, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10201", "display_name": "Speech Recognition and Synthesis", "score": 0.996999979019165, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/conditional-random-field", "display_name": "Conditional random field", "score": 0.9066014289855957}, {"id": "https://openalex.org/keywords/crfs", "display_name": "CRFS", "score": 0.8998609781265259}, {"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.7753100395202637}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.6968623995780945}, {"id": "https://openalex.org/keywords/word", "display_name": "Word (group theory)", "score": 0.667824387550354}, {"id": "https://openalex.org/keywords/segmentation", "display_name": "Segmentation", "score": 0.6114587783813477}, {"id": "https://openalex.org/keywords/natural-language-processing", "display_name": "Natural language processing", "score": 0.6054441332817078}, {"id": "https://openalex.org/keywords/sequence-labeling", "display_name": "Sequence labeling", "score": 0.6020126938819885}, {"id": "https://openalex.org/keywords/probabilistic-logic", "display_name": "Probabilistic logic", "score": 0.574987530708313}, {"id": "https://openalex.org/keywords/text-segmentation", "display_name": "Text segmentation", "score": 0.5620797872543335}, {"id": "https://openalex.org/keywords/pattern-recognition", "display_name": "Pattern recognition (psychology)", "score": 0.4473086893558502}, {"id": "https://openalex.org/keywords/sequence", "display_name": "Sequence (biology)", "score": 0.4448122978210449}, {"id": "https://openalex.org/keywords/domain", "display_name": "Domain (mathematical analysis)", "score": 0.4437868595123291}, {"id": "https://openalex.org/keywords/mathematics", "display_name": "Mathematics", "score": 0.119850754737854}], "concepts": [{"id": "https://openalex.org/C152565575", "wikidata": "https://www.wikidata.org/wiki/Q1124538", "display_name": "Conditional random field", "level": 2, "score": 0.9066014289855957}, {"id": "https://openalex.org/C2775953691", "wikidata": "https://www.wikidata.org/wiki/Q5013874", "display_name": "CRFS", "level": 3, "score": 0.8998609781265259}, {"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.7753100395202637}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.6968623995780945}, {"id": "https://openalex.org/C90805587", "wikidata": "https://www.wikidata.org/wiki/Q10944557", "display_name": "Word (group theory)", "level": 2, "score": 0.667824387550354}, {"id": "https://openalex.org/C89600930", "wikidata": "https://www.wikidata.org/wiki/Q1423946", "display_name": "Segmentation", "level": 2, "score": 0.6114587783813477}, {"id": "https://openalex.org/C204321447", "wikidata": "https://www.wikidata.org/wiki/Q30642", "display_name": "Natural language processing", "level": 1, "score": 0.6054441332817078}, {"id": "https://openalex.org/C35639132", "wikidata": "https://www.wikidata.org/wiki/Q7452468", "display_name": "Sequence labeling", "level": 3, "score": 0.6020126938819885}, {"id": "https://openalex.org/C49937458", "wikidata": "https://www.wikidata.org/wiki/Q2599292", "display_name": "Probabilistic logic", "level": 2, "score": 0.574987530708313}, {"id": "https://openalex.org/C98501671", "wikidata": "https://www.wikidata.org/wiki/Q1948408", "display_name": "Text segmentation", "level": 3, "score": 0.5620797872543335}, {"id": "https://openalex.org/C153180895", "wikidata": "https://www.wikidata.org/wiki/Q7148389", "display_name": "Pattern recognition (psychology)", "level": 2, "score": 0.4473086893558502}, {"id": "https://openalex.org/C2778112365", "wikidata": "https://www.wikidata.org/wiki/Q3511065", "display_name": "Sequence (biology)", "level": 2, "score": 0.4448122978210449}, {"id": "https://openalex.org/C36503486", "wikidata": "https://www.wikidata.org/wiki/Q11235244", "display_name": "Domain (mathematical analysis)", "level": 2, "score": 0.4437868595123291}, {"id": "https://openalex.org/C33923547", "wikidata": "https://www.wikidata.org/wiki/Q395", "display_name": "Mathematics", "level": 0, "score": 0.119850754737854}, {"id": "https://openalex.org/C134306372", "wikidata": "https://www.wikidata.org/wiki/Q7754", "display_name": "Mathematical analysis", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C2524010", "wikidata": "https://www.wikidata.org/wiki/Q8087", "display_name": "Geometry", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C2780451532", "wikidata": "https://www.wikidata.org/wiki/Q759676", "display_name": "Task (project management)", "level": 2, "score": 0.0}, {"id": "https://openalex.org/C162324750", "wikidata": "https://www.wikidata.org/wiki/Q8134", "display_name": "Economics", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C86803240", "wikidata": "https://www.wikidata.org/wiki/Q420", "display_name": "Biology", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C187736073", "wikidata": "https://www.wikidata.org/wiki/Q2920921", "display_name": "Management", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C54355233", "wikidata": "https://www.wikidata.org/wiki/Q7162", "display_name": "Genetics", "level": 1, "score": 0.0}], "mesh": [], "locations_count": 10, "locations": [{"id": "doi:10.3115/1220355.1220436", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1220355.1220436", "pdf_url": "https://dl.acm.org/doi/pdf/10.3115/1220355.1220436", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the 20th international conference on Computational Linguistics - COLING '04", "raw_type": "proceedings-article"}, {"id": "pmh:oai:scholarworks.umass.edu:cs_faculty_pubs-1091", "is_oa": false, "landing_page_url": "https://scholarworks.umass.edu/cs_faculty_pubs/92", "pdf_url": null, "source": {"id": "https://openalex.org/S4306402240", "display_name": "ScholarWorks@UMassAmherst (University of Massachusetts Amherst)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I24603500", "host_organization_name": "University of Massachusetts Amherst", "host_organization_lineage": ["https://openalex.org/I24603500"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Computer Science Department Faculty Publication Series", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.1006.743", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1006.743", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://scholarworks.umass.edu/cgi/viewcontent.cgi?article%3D1091%26context%3Dcs_faculty_pubs", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.137.3583", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.137.3583", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cs.umass.edu/~mccallum/papers/coling04.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.152.2063", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.152.2063", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://ciir.cs.umass.edu/pubfiles/ir-363.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.3.1083", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.3.1083", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.people.umass.edu/fuchun/publication/coling2004.ps", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.594.5974", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.594.5974", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cs.ait.ac.th/~mdailey/cvreadings/Peng-ChineseSegmentation.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.993.5909", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.993.5909", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "https://works.bepress.com/andrew_mccallum/43/download/", "raw_type": "text"}, {"id": "pmh:oai:scholarworks.umass.edu:20.500.14394/10506", "is_oa": false, "landing_page_url": "https://hdl.handle.net/20.500.14394/10506", "pdf_url": null, "source": {"id": "https://openalex.org/S4306402057", "display_name": "Scholarworks (University of Massachusetts Amherst)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I24603500", "host_organization_name": "University of Massachusetts Amherst", "host_organization_lineage": ["https://openalex.org/I24603500"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "published", "raw_type": "Article"}, {"id": "pmh:oai:works.bepress.com:andrew_mccallum-1061", "is_oa": false, "landing_page_url": "https://works.bepress.com/andrew_mccallum/43", "pdf_url": null, "source": {"id": "https://openalex.org/S4306402057", "display_name": "Scholarworks (University of Massachusetts Amherst)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I24603500", "host_organization_name": "University of Massachusetts Amherst", "host_organization_lineage": ["https://openalex.org/I24603500"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Andrew McCallum", "raw_type": "text"}], "best_oa_location": {"id": "doi:10.3115/1220355.1220436", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1220355.1220436", "pdf_url": "https://dl.acm.org/doi/pdf/10.3115/1220355.1220436", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the 20th international conference on Computational Linguistics - COLING '04", "raw_type": "proceedings-article"}, "sustainable_development_goals": [{"display_name": "Quality Education", "score": 0.5400000214576721, "id": "https://metadata.un.org/sdg/4"}], "awards": [{"id": "https://openalex.org/G7704502625", "display_name": "ITR:     Unified Graphical Models of Information Extraction and Data Mining with Application to Social Network Analysis", "funder_award_id": "0326249", "funder_id": "https://openalex.org/F4320306076", "funder_display_name": "National Science Foundation"}], "funders": [{"id": "https://openalex.org/F4320306076", "display_name": "National Science Foundation", "ror": "https://ror.org/021nxhr62"}, {"id": "https://openalex.org/F4320311089", "display_name": "National Security Agency", "ror": "https://ror.org/0047bvr32"}], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2036516910.pdf", "grobid_xml": "https://content.openalex.org/works/W2036516910.grobid-xml"}, "referenced_works_count": 23, "referenced_works": ["https://openalex.org/W1518670641", "https://openalex.org/W1524975733", "https://openalex.org/W1534730506", "https://openalex.org/W1564640168", "https://openalex.org/W1586407478", "https://openalex.org/W1980925709", "https://openalex.org/W2033295622", "https://openalex.org/W2036701977", "https://openalex.org/W2059044879", "https://openalex.org/W2102667697", "https://openalex.org/W2108220507", "https://openalex.org/W2116317530", "https://openalex.org/W2120814856", "https://openalex.org/W2125838338", "https://openalex.org/W2147880316", "https://openalex.org/W2156515921", "https://openalex.org/W2160842254", "https://openalex.org/W2163377725", "https://openalex.org/W2420187884", "https://openalex.org/W2911427979", "https://openalex.org/W3145501851", "https://openalex.org/W4253573210", "https://openalex.org/W4285719527"], "related_works": ["https://openalex.org/W2962906565", "https://openalex.org/W2798423868", "https://openalex.org/W3015678144", "https://openalex.org/W2076440176", "https://openalex.org/W2055466819", "https://openalex.org/W2140585957", "https://openalex.org/W2054134081", "https://openalex.org/W1675450783", "https://openalex.org/W2061027419", "https://openalex.org/W189110383"], "abstract_inverted_index": {"Chinese": [0, 28, 79], "word": [1, 29, 60, 80], "segmentation": [2, 30, 81], "is": [3, 69, 85], "a": [4, 33, 57, 76], "difficult,": [5], "important": [6], "and": [7, 26, 52], "widely-studied": [8], "sequence": [9], "modeling": [10], "problem.": [11], "This": [12], "paper": [13], "demonstrates": [14], "the": [15, 39, 45], "ability": [16], "of": [17, 41, 47, 50], "linear-chain": [18], "conditional": [19], "random": [20], "fields": [21], "(CRFs)": [22], "to": [23], "perform": [24], "robust": [25], "accurate": [27], "by": [31], "providing": [32], "principled": [34], "framework": [35], "that": [36], "easily": [37], "supports": [38], "integration": [40], "domain": [42], "knowledge": [43], "in": [44, 75], "form": [46], "multiple": [48], "lexicons": [49], "characters": [51], "words.": [53], "We": [54], "also": [55], "present": [56], "probabilistic": [58], "new": [59], "detection": [61], "method,": [62], "which": [63], "further": [64], "improves": [65], "performance.": [66], "Our": [67], "system": [68], "evaluated": [70], "on": [71], "four": [72], "datasets": [73], "used": [74], "recent": [77], "comprehensive": [78], "competition.": [82], "State-of-the-art": [83], "performance": [84], "obtained.": [86]}, "counts_by_year": [{"year": 2025, "cited_by_count": 5}, {"year": 2024, "cited_by_count": 6}, {"year": 2023, "cited_by_count": 5}, {"year": 2022, "cited_by_count": 12}, {"year": 2021, "cited_by_count": 14}, {"year": 2020, "cited_by_count": 31}, {"year": 2019, "cited_by_count": 34}, {"year": 2018, "cited_by_count": 39}, {"year": 2017, "cited_by_count": 25}, {"year": 2016, "cited_by_count": 27}, {"year": 2015, "cited_by_count": 23}, {"year": 2014, "cited_by_count": 30}, {"year": 2013, "cited_by_count": 38}, {"year": 2012, "cited_by_count": 28}], "updated_date": "2026-08-01T09:00:35.917206", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W2084341220", "doi": "https://doi.org/10.1214/ss/1009213726", "title": "Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author)", "display_name": "Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author)", "relevance_score": 555.6413, "publication_year": 2001, "publication_date": "2001-08-01", "ids": {"openalex": "https://openalex.org/W2084341220", "doi": "https://doi.org/10.1214/ss/1009213726", "mag": "2084341220"}, "language": "en", "primary_location": {"id": "doi:10.1214/ss/1009213726", "is_oa": true, "landing_page_url": "https://doi.org/10.1214/ss/1009213726", "pdf_url": "https://projecteuclid.org/journals/statistical-science/volume-16/issue-3/Statistical-Modeling--The-Two-Cultures-with-comments-and-a/10.1214/ss/1009213726.pdf", "source": {"id": "https://openalex.org/S12967704", "display_name": "Statistical Science", "issn_l": "0883-4237", "issn": ["0883-4237", "2168-8745"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310319881", "host_organization_name": "Institute of Mathematical Statistics", "host_organization_lineage": ["https://openalex.org/P4310319881"], "host_organization_lineage_names": ["Institute of Mathematical Statistics"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Statistical Science", "raw_type": "journal-article"}, "type": "article", "indexed_in": ["crossref"], "open_access": {"is_oa": true, "oa_status": "bronze", "oa_url": "https://projecteuclid.org/journals/statistical-science/volume-16/issue-3/Statistical-Modeling--The-Two-Cultures-with-comments-and-a/10.1214/ss/1009213726.pdf", "any_repository_has_fulltext": false}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5039125390", "display_name": "Leo Breiman", "orcid": null}, "institutions": [], "countries": [], "is_corresponding": true, "raw_author_name": "Leo Breiman", "raw_affiliation_strings": [], "raw_orcid": null, "affiliations": []}], "institutions": [], "countries_distinct_count": 0, "institutions_distinct_count": 0, "corresponding_author_ids": ["https://openalex.org/A5039125390"], "corresponding_institution_ids": [], "apc_list": null, "apc_paid": null, "fwci": 34.5032, "has_fulltext": true, "cited_by_count": 4318, "citation_normalized_percentile": {"value": 0.99700902, "is_in_top_1_percent": true, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 99, "max": 100}, "biblio": {"volume": "16", "issue": "3", "first_page": null, "last_page": null}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T11303", "display_name": "Bayesian Modeling and Causal Inference", "score": 0.9968000054359436, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T11303", "display_name": "Bayesian Modeling and Causal Inference", "score": 0.9968000054359436, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T11871", "display_name": "Advanced Statistical Methods and Models", "score": 0.9955000281333923, "subfield": {"id": "https://openalex.org/subfields/2613", "display_name": "Statistics and Probability"}, "field": {"id": "https://openalex.org/fields/26", "display_name": "Mathematics"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10136", "display_name": "Statistical Methods and Inference", "score": 0.9951000213623047, "subfield": {"id": "https://openalex.org/subfields/2613", "display_name": "Statistics and Probability"}, "field": {"id": "https://openalex.org/fields/26", "display_name": "Mathematics"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.7124022245407104}, {"id": "https://openalex.org/keywords/data-set", "display_name": "Data set", "score": 0.5968297123908997}, {"id": "https://openalex.org/keywords/field", "display_name": "Field (mathematics)", "score": 0.5885418057441711}, {"id": "https://openalex.org/keywords/statistical-model", "display_name": "Statistical model", "score": 0.5721044540405273}, {"id": "https://openalex.org/keywords/set", "display_name": "Set (abstract data type)", "score": 0.5571048855781555}, {"id": "https://openalex.org/keywords/range", "display_name": "Range (aeronautics)", "score": 0.5403786301612854}, {"id": "https://openalex.org/keywords/data-science", "display_name": "Data science", "score": 0.4409579634666443}, {"id": "https://openalex.org/keywords/statistical-theory", "display_name": "Statistical theory", "score": 0.4367968440055847}, {"id": "https://openalex.org/keywords/econometrics", "display_name": "Econometrics", "score": 0.40862929821014404}, {"id": "https://openalex.org/keywords/data-mining", "display_name": "Data mining", "score": 0.39252740144729614}, {"id": "https://openalex.org/keywords/machine-learning", "display_name": "Machine learning", "score": 0.3108782172203064}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.26027798652648926}, {"id": "https://openalex.org/keywords/statistics", "display_name": "Statistics", "score": 0.20747491717338562}, {"id": "https://openalex.org/keywords/mathematics", "display_name": "Mathematics", "score": 0.18535473942756653}], "concepts": [{"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.7124022245407104}, {"id": "https://openalex.org/C58489278", "wikidata": "https://www.wikidata.org/wiki/Q1172284", "display_name": "Data set", "level": 2, "score": 0.5968297123908997}, {"id": "https://openalex.org/C9652623", "wikidata": "https://www.wikidata.org/wiki/Q190109", "display_name": "Field (mathematics)", "level": 2, "score": 0.5885418057441711}, {"id": "https://openalex.org/C114289077", "wikidata": "https://www.wikidata.org/wiki/Q3284399", "display_name": "Statistical model", "level": 2, "score": 0.5721044540405273}, {"id": "https://openalex.org/C177264268", "wikidata": "https://www.wikidata.org/wiki/Q1514741", "display_name": "Set (abstract data type)", "level": 2, "score": 0.5571048855781555}, {"id": "https://openalex.org/C204323151", "wikidata": "https://www.wikidata.org/wiki/Q905424", "display_name": "Range (aeronautics)", "level": 2, "score": 0.5403786301612854}, {"id": "https://openalex.org/C2522767166", "wikidata": "https://www.wikidata.org/wiki/Q2374463", "display_name": "Data science", "level": 1, "score": 0.4409579634666443}, {"id": "https://openalex.org/C48057537", "wikidata": "https://www.wikidata.org/wiki/Q3551145", "display_name": "Statistical theory", "level": 2, "score": 0.4367968440055847}, {"id": "https://openalex.org/C149782125", "wikidata": "https://www.wikidata.org/wiki/Q160039", "display_name": "Econometrics", "level": 1, "score": 0.40862929821014404}, {"id": "https://openalex.org/C124101348", "wikidata": "https://www.wikidata.org/wiki/Q172491", "display_name": "Data mining", "level": 1, "score": 0.39252740144729614}, {"id": "https://openalex.org/C119857082", "wikidata": "https://www.wikidata.org/wiki/Q2539", "display_name": "Machine learning", "level": 1, "score": 0.3108782172203064}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.26027798652648926}, {"id": "https://openalex.org/C105795698", "wikidata": "https://www.wikidata.org/wiki/Q12483", "display_name": "Statistics", "level": 1, "score": 0.20747491717338562}, {"id": "https://openalex.org/C33923547", "wikidata": "https://www.wikidata.org/wiki/Q395", "display_name": "Mathematics", "level": 0, "score": 0.18535473942756653}, {"id": "https://openalex.org/C202444582", "wikidata": "https://www.wikidata.org/wiki/Q837863", "display_name": "Pure mathematics", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C159985019", "wikidata": "https://www.wikidata.org/wiki/Q181790", "display_name": "Composite material", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C192562407", "wikidata": "https://www.wikidata.org/wiki/Q228736", "display_name": "Materials science", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C199360897", "wikidata": "https://www.wikidata.org/wiki/Q9143", "display_name": "Programming language", "level": 1, "score": 0.0}], "mesh": [], "locations_count": 2, "locations": [{"id": "doi:10.1214/ss/1009213726", "is_oa": true, "landing_page_url": "https://doi.org/10.1214/ss/1009213726", "pdf_url": "https://projecteuclid.org/journals/statistical-science/volume-16/issue-3/Statistical-Modeling--The-Two-Cultures-with-comments-and-a/10.1214/ss/1009213726.pdf", "source": {"id": "https://openalex.org/S12967704", "display_name": "Statistical Science", "issn_l": "0883-4237", "issn": ["0883-4237", "2168-8745"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310319881", "host_organization_name": "Institute of Mathematical Statistics", "host_organization_lineage": ["https://openalex.org/P4310319881"], "host_organization_lineage_names": ["Institute of Mathematical Statistics"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Statistical Science", "raw_type": "journal-article"}, {"id": "pmh:oai:CULeuclid:euclid.ss/1009213726", "is_oa": false, "landing_page_url": "http://projecteuclid.org/euclid.ss/1009213726", "pdf_url": null, "source": {"id": "https://openalex.org/S4306400787", "display_name": "Project Euclid (Cornell University)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I205783295", "host_organization_name": "Cornell University", "host_organization_lineage": ["https://openalex.org/I205783295"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "", "raw_type": "Text"}], "best_oa_location": {"id": "doi:10.1214/ss/1009213726", "is_oa": true, "landing_page_url": "https://doi.org/10.1214/ss/1009213726", "pdf_url": "https://projecteuclid.org/journals/statistical-science/volume-16/issue-3/Statistical-Modeling--The-Two-Cultures-with-comments-and-a/10.1214/ss/1009213726.pdf", "source": {"id": "https://openalex.org/S12967704", "display_name": "Statistical Science", "issn_l": "0883-4237", "issn": ["0883-4237", "2168-8745"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310319881", "host_organization_name": "Institute of Mathematical Statistics", "host_organization_lineage": ["https://openalex.org/P4310319881"], "host_organization_lineage_names": ["Institute of Mathematical Statistics"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Statistical Science", "raw_type": "journal-article"}, "sustainable_development_goals": [{"display_name": "Partnerships for the goals", "score": 0.5, "id": "https://metadata.un.org/sdg/17"}], "awards": [], "funders": [], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2084341220.pdf", "grobid_xml": "https://content.openalex.org/works/W2084341220.grobid-xml"}, "referenced_works_count": 27, "referenced_works": ["https://openalex.org/W1554104828", "https://openalex.org/W1761022139", "https://openalex.org/W1973967548", "https://openalex.org/W2024046085", "https://openalex.org/W2032566985", "https://openalex.org/W2067885219", "https://openalex.org/W2084011590", "https://openalex.org/W2093281118", "https://openalex.org/W2096316000", "https://openalex.org/W2112081648", "https://openalex.org/W2113242816", "https://openalex.org/W2120240539", "https://openalex.org/W2129378933", "https://openalex.org/W2142334564", "https://openalex.org/W2156909104", "https://openalex.org/W2911964244", "https://openalex.org/W4233960047", "https://openalex.org/W4242234769", "https://openalex.org/W4248624814", "https://openalex.org/W4255405844", "https://openalex.org/W4298876635", "https://openalex.org/W4301861531", "https://openalex.org/W6603394685", "https://openalex.org/W6636118231", "https://openalex.org/W6676769703", "https://openalex.org/W6843735874", "https://openalex.org/W7071374342"], "related_works": ["https://openalex.org/W2359049220", "https://openalex.org/W2970045733", "https://openalex.org/W4206224896", "https://openalex.org/W2988555347", "https://openalex.org/W179069106", "https://openalex.org/W2296507500", "https://openalex.org/W1997578814", "https://openalex.org/W2482105717", "https://openalex.org/W4232513139", "https://openalex.org/W2423242616"], "abstract_inverted_index": {"There": [0], "are": [1, 20], "two": [2], "cultures": [3], "in": [4, 80, 87], "the": [5, 18, 35, 47], "use": [6, 50, 124], "of": [7, 51, 73, 147], "statistical": [8, 41], "modeling": [9, 111], "to": [10, 46, 58, 109, 123, 126, 132], "reach": [11], "conclusions": [12], "from": [13, 67, 135], "data.": [14], "One": [15], "assumes": [16], "that": [17], "data": [19, 26, 36, 52, 99, 110, 114, 125, 139], "generated": [21], "by": [22], "a": [23, 70, 103, 120, 143], "given": [24], "stochastic": [25], "model.": [27], "The": [28, 40], "other": [29], "uses": [30], "algorithmic": [31], "models": [32, 140], "and": [33, 63, 82, 101, 106, 141], "treats": [34], "mechanism": [37], "as": [38, 102, 119], "unknown.": [39], "community": [42], "has": [43, 56, 64, 84], "been": [44], "committed": [45], "almost": [48], "exclusive": [49, 136], "models.": [53], "This": [54], "commitment": [55], "led": [57], "irrelevant": [59], "theory,": [60], "questionable": [61], "conclusions,": [62], "kept": [65], "statisticians": [66], "working": [68], "on": [69, 96, 112, 138], "large": [71, 97], "range": [72], "interesting": [74], "current": [75], "problems.": [76], "Algorithmic": [77], "modeling,": [78], "both": [79, 95], "theory": [81], "practice,": [83], "developed": [85], "rapidly": [86], "fields": [88], "outside": [89], "statistics.": [90], "It": [91], "can": [92], "be": [93], "used": [94], "complex": [98], "sets": [100], "more": [104, 144], "accurate": [105], "informative": [107], "alternative": [108], "smaller": [113], "sets.": [115], "If": [116], "our": [117], "goal": [118], "field": [121], "is": [122], "solve": [127], "problems,": [128], "then": [129], "we": [130], "need": [131], "move": [133], "away": [134], "dependence": [137], "adopt": [142], "diverse": [145], "set": [146], "tools.": [148]}, "counts_by_year": [{"year": 2026, "cited_by_count": 215}, {"year": 2025, "cited_by_count": 362}, {"year": 2024, "cited_by_count": 362}, {"year": 2023, "cited_by_count": 369}, {"year": 2022, "cited_by_count": 404}, {"year": 2021, "cited_by_count": 490}, {"year": 2020, "cited_by_count": 406}, {"year": 2019, "cited_by_count": 311}, {"year": 2018, "cited_by_count": 259}, {"year": 2017, "cited_by_count": 187}, {"year": 2016, "cited_by_count": 145}, {"year": 2015, "cited_by_count": 147}, {"year": 2014, "cited_by_count": 99}, {"year": 2013, "cited_by_count": 85}, {"year": 2012, "cited_by_count": 91}], "updated_date": "2026-08-06T08:24:18.245995", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W2096765155", "doi": "https://doi.org/10.3115/1219840.1219885", "title": "Incorporating non-local information into information extraction systems by Gibbs sampling", "display_name": "Incorporating non-local information into information extraction systems by Gibbs sampling", "relevance_score": 547.3124, "publication_year": 2005, "publication_date": "2005-01-01", "ids": {"openalex": "https://openalex.org/W2096765155", "doi": "https://doi.org/10.3115/1219840.1219885", "mag": "2096765155"}, "language": "en", "primary_location": {"id": "doi:10.3115/1219840.1219885", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1219840.1219885", "pdf_url": "http://dl.acm.org/ft_gateway.cfm?id=1219885&type=pdf", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics - ACL '05", "raw_type": "proceedings-article"}, "type": "conference-paper", "indexed_in": ["crossref"], "open_access": {"is_oa": true, "oa_status": "gold", "oa_url": "http://dl.acm.org/ft_gateway.cfm?id=1219885&type=pdf", "any_repository_has_fulltext": null}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5023694822", "display_name": "Jenny Rose Finkel", "orcid": null}, "institutions": [{"id": "https://openalex.org/I97018004", "display_name": "Stanford University", "ror": "https://ror.org/00f54p054", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I97018004"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Jenny Rose Finkel", "raw_affiliation_strings": ["Stanford University, Stanford, CA", "Stanford University Stanford CA"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Stanford University, Stanford, CA", "institution_ids": ["https://openalex.org/I97018004"]}, {"raw_affiliation_string": "Stanford University Stanford CA", "institution_ids": ["https://openalex.org/I97018004"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5002013404", "display_name": "Trond Grenager", "orcid": null}, "institutions": [{"id": "https://openalex.org/I97018004", "display_name": "Stanford University", "ror": "https://ror.org/00f54p054", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I97018004"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Trond Grenager", "raw_affiliation_strings": ["Stanford University, Stanford, CA", "Stanford University Stanford CA"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Stanford University, Stanford, CA", "institution_ids": ["https://openalex.org/I97018004"]}, {"raw_affiliation_string": "Stanford University Stanford CA", "institution_ids": ["https://openalex.org/I97018004"]}]}, {"author_position": "last", "author": {"id": "https://openalex.org/A5046006076", "display_name": "Christopher D. Manning", "orcid": "https://orcid.org/0000-0001-6155-649X"}, "institutions": [{"id": "https://openalex.org/I97018004", "display_name": "Stanford University", "ror": "https://ror.org/00f54p054", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I97018004"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Christopher Manning", "raw_affiliation_strings": ["Stanford University, Stanford, CA", "Stanford University Stanford CA"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Stanford University, Stanford, CA", "institution_ids": ["https://openalex.org/I97018004"]}, {"raw_affiliation_string": "Stanford University Stanford CA", "institution_ids": ["https://openalex.org/I97018004"]}]}], "institutions": [], "countries_distinct_count": 1, "institutions_distinct_count": 1, "corresponding_author_ids": [], "corresponding_institution_ids": ["https://openalex.org/I97018004"], "apc_list": null, "apc_paid": null, "fwci": 19.9628, "has_fulltext": true, "cited_by_count": 3038, "citation_normalized_percentile": {"value": 0.99661031, "is_in_top_1_percent": true, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 99, "max": 100}, "biblio": {"volume": null, "issue": null, "first_page": "363", "last_page": "370"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9995999932289124, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9995999932289124, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T12072", "display_name": "Machine Learning and Algorithms", "score": 0.9993000030517578, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 0.9991999864578247, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.7829605340957642}, {"id": "https://openalex.org/keywords/gibbs-sampling", "display_name": "Gibbs sampling", "score": 0.5593608021736145}, {"id": "https://openalex.org/keywords/information-extraction", "display_name": "Information extraction", "score": 0.5453944802284241}, {"id": "https://openalex.org/keywords/viterbi-algorithm", "display_name": "Viterbi algorithm", "score": 0.5360332727432251}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.5005412101745605}, {"id": "https://openalex.org/keywords/approximate-inference", "display_name": "Approximate inference", "score": 0.49393683671951294}, {"id": "https://openalex.org/keywords/inference", "display_name": "Inference", "score": 0.483721524477005}, {"id": "https://openalex.org/keywords/probabilistic-logic", "display_name": "Probabilistic logic", "score": 0.4789346158504486}, {"id": "https://openalex.org/keywords/hidden-markov-model", "display_name": "Hidden Markov model", "score": 0.4399802088737488}, {"id": "https://openalex.org/keywords/machine-learning", "display_name": "Machine learning", "score": 0.37418508529663086}, {"id": "https://openalex.org/keywords/data-mining", "display_name": "Data mining", "score": 0.3540502190589905}, {"id": "https://openalex.org/keywords/algorithm", "display_name": "Algorithm", "score": 0.33569401502609253}, {"id": "https://openalex.org/keywords/bayesian-probability", "display_name": "Bayesian probability", "score": 0.28122222423553467}], "concepts": [{"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.7829605340957642}, {"id": "https://openalex.org/C158424031", "wikidata": "https://www.wikidata.org/wiki/Q1191905", "display_name": "Gibbs sampling", "level": 3, "score": 0.5593608021736145}, {"id": "https://openalex.org/C195807954", "wikidata": "https://www.wikidata.org/wiki/Q1662562", "display_name": "Information extraction", "level": 2, "score": 0.5453944802284241}, {"id": "https://openalex.org/C60582962", "wikidata": "https://www.wikidata.org/wiki/Q83886", "display_name": "Viterbi algorithm", "level": 3, "score": 0.5360332727432251}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.5005412101745605}, {"id": "https://openalex.org/C2777472644", "wikidata": "https://www.wikidata.org/wiki/Q16968992", "display_name": "Approximate inference", "level": 3, "score": 0.49393683671951294}, {"id": "https://openalex.org/C2776214188", "wikidata": "https://www.wikidata.org/wiki/Q408386", "display_name": "Inference", "level": 2, "score": 0.483721524477005}, {"id": "https://openalex.org/C49937458", "wikidata": "https://www.wikidata.org/wiki/Q2599292", "display_name": "Probabilistic logic", "level": 2, "score": 0.4789346158504486}, {"id": "https://openalex.org/C23224414", "wikidata": "https://www.wikidata.org/wiki/Q176769", "display_name": "Hidden Markov model", "level": 2, "score": 0.4399802088737488}, {"id": "https://openalex.org/C119857082", "wikidata": "https://www.wikidata.org/wiki/Q2539", "display_name": "Machine learning", "level": 1, "score": 0.37418508529663086}, {"id": "https://openalex.org/C124101348", "wikidata": "https://www.wikidata.org/wiki/Q172491", "display_name": "Data mining", "level": 1, "score": 0.3540502190589905}, {"id": "https://openalex.org/C11413529", "wikidata": "https://www.wikidata.org/wiki/Q8366", "display_name": "Algorithm", "level": 1, "score": 0.33569401502609253}, {"id": "https://openalex.org/C107673813", "wikidata": "https://www.wikidata.org/wiki/Q812534", "display_name": "Bayesian probability", "level": 2, "score": 0.28122222423553467}], "mesh": [], "locations_count": 5, "locations": [{"id": "doi:10.3115/1219840.1219885", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1219840.1219885", "pdf_url": "http://dl.acm.org/ft_gateway.cfm?id=1219885&type=pdf", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics - ACL '05", "raw_type": "proceedings-article"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.131.8904", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.131.8904", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://acl.ldc.upenn.edu/p/p05/p05-1045.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.420.8263", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.420.8263", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://nlp.stanford.edu/~grenager/papers/gibbscrf3-1.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.77.7532", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.77.7532", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.stanford.edu/~grenager/papers/gibbscrf3.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.80.8813", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.80.8813", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://nlp.stanford.edu/cmanning/papers/gibbscrf3.pdf", "raw_type": "text"}], "best_oa_location": {"id": "doi:10.3115/1219840.1219885", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1219840.1219885", "pdf_url": "http://dl.acm.org/ft_gateway.cfm?id=1219885&type=pdf", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics - ACL '05", "raw_type": "proceedings-article"}, "sustainable_development_goals": [{"display_name": "Quality Education", "score": 0.6499999761581421, "id": "https://metadata.un.org/sdg/4"}], "awards": [], "funders": [{"id": "https://openalex.org/F4320323106", "display_name": "Agricultural Research Development Agency", "ror": "https://ror.org/01shbv660"}], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2096765155.pdf", "grobid_xml": "https://content.openalex.org/works/W2096765155.grobid-xml"}, "referenced_works_count": 25, "referenced_works": ["https://openalex.org/W1505083828", "https://openalex.org/W1513861746", "https://openalex.org/W1734853756", "https://openalex.org/W1979960035", "https://openalex.org/W1982982698", "https://openalex.org/W1996339514", "https://openalex.org/W1999595522", "https://openalex.org/W2004111828", "https://openalex.org/W2004384146", "https://openalex.org/W2020999234", "https://openalex.org/W2024060531", "https://openalex.org/W2028122758", "https://openalex.org/W2045993505", "https://openalex.org/W2125838338", "https://openalex.org/W2129712609", "https://openalex.org/W2135194391", "https://openalex.org/W2145948275", "https://openalex.org/W2147880316", "https://openalex.org/W2152455533", "https://openalex.org/W2160842254", "https://openalex.org/W2163915185", "https://openalex.org/W2171776966", "https://openalex.org/W2962735828", "https://openalex.org/W4253573210", "https://openalex.org/W4302422232"], "related_works": ["https://openalex.org/W2136652457", "https://openalex.org/W2169849734", "https://openalex.org/W2116722627", "https://openalex.org/W2129150969", "https://openalex.org/W2236912844", "https://openalex.org/W1975869217", "https://openalex.org/W2401728283", "https://openalex.org/W2383829109", "https://openalex.org/W2379938888", "https://openalex.org/W2386035178"], "abstract_inverted_index": {"Most": [0], "current": [1], "statistical": [2], "natural": [3], "language": [4, 36], "processing": [5], "models": [6, 73], "use": [7, 92], "only": [8], "local": [9], "features": [10], "so": [11], "as": [12, 75], "to": [13, 24, 41, 54, 83, 95, 124], "permit": [14], "dynamic": [15], "programming": [16], "in": [17, 35, 58, 66, 71, 118], "inference,": [18], "but": [19], "this": [20, 43, 93], "makes": [21], "them": [22], "unable": [23], "fully": [25], "account": [26], "for": [27], "the": [28], "long": [29], "distance": [30], "structure": [31, 86], "that": [32], "is": [33, 81], "prevalent": [34], "use.": [37], "We": [38, 91], "show": [39], "how": [40], "solve": [42], "dilemma": [44], "with": [45, 103], "Gibbs": [46], "sampling,": [47], "a": [48], "simple": [49], "Monte": [50], "Carlo": [51], "method": [52], "used": [53], "perform": [55], "approximate": [56], "inference": [57], "factored": [59], "probabilistic": [60], "models.": [61], "By": [62], "using": [63], "simulated": [64], "annealing": [65], "place": [67], "of": [68, 122], "Viterbi": [69], "decoding": [70], "sequence": [72], "such": [74], "HMMs,": [76], "CMMs,": [77], "and": [78, 110], "CRFs,": [79], "it": [80], "possible": [82], "incorporate": [84], "non-local": [85], "while": [87], "preserving": [88], "tractable": [89], "inference.": [90], "technique": [94, 116], "augment": [96], "an": [97, 119], "existing": [98], "CRF-based": [99], "information": [100, 132], "extraction": [101, 111, 133], "system": [102], "long-distance": [104], "dependency": [105], "models,": [106], "enforcing": [107], "label": [108], "consistency": [109, 113], "template": [112], "constraints.": [114], "This": [115], "results": [117], "error": [120], "reduction": [121], "up": [123], "9%": [125], "over": [126], "state-of-the-art": [127], "systems": [128], "on": [129], "two": [130], "established": [131], "tasks.": [134]}, "counts_by_year": [{"year": 2026, "cited_by_count": 6}, {"year": 2025, "cited_by_count": 23}, {"year": 2024, "cited_by_count": 48}, {"year": 2023, "cited_by_count": 79}, {"year": 2022, "cited_by_count": 99}, {"year": 2021, "cited_by_count": 169}, {"year": 2020, "cited_by_count": 249}, {"year": 2019, "cited_by_count": 246}, {"year": 2018, "cited_by_count": 280}, {"year": 2017, "cited_by_count": 260}, {"year": 2016, "cited_by_count": 242}, {"year": 2015, "cited_by_count": 234}, {"year": 2014, "cited_by_count": 269}, {"year": 2013, "cited_by_count": 248}, {"year": 2012, "cited_by_count": 194}], "updated_date": "2026-07-29T14:22:42.915294", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W1516111018", "doi": "https://doi.org/10.1023/a:1007665907178", "title": "An Introduction to Variational Methods for Graphical Models", "display_name": "An Introduction to Variational Methods for Graphical Models", "relevance_score": 545.05585, "publication_year": 1999, "publication_date": "1999-11-01", "ids": {"openalex": "https://openalex.org/W1516111018", "doi": "https://doi.org/10.1023/a:1007665907178", "mag": "1516111018"}, "language": "en", "primary_location": {"id": "doi:10.1023/a:1007665907178", "is_oa": true, "landing_page_url": "https://doi.org/10.1023/a:1007665907178", "pdf_url": "https://link.springer.com/content/pdf/10.1023/A:1007665907178.pdf", "source": {"id": "https://openalex.org/S62148650", "display_name": "Machine Learning", "issn_l": "0885-6125", "issn": ["0885-6125", "1573-0565"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310319900", "host_organization_name": "Springer Science+Business Media", "host_organization_lineage": ["https://openalex.org/P4310319900", "https://openalex.org/P4310319965"], "host_organization_lineage_names": ["Springer Science+Business Media", "Springer Nature"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Machine Learning", "raw_type": "journal-article"}, "type": "article", "indexed_in": ["crossref"], "open_access": {"is_oa": true, "oa_status": "bronze", "oa_url": "https://link.springer.com/content/pdf/10.1023/A:1007665907178.pdf", "any_repository_has_fulltext": false}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5049812527", "display_name": "Michael I. Jordan", "orcid": "https://orcid.org/0000-0001-8935-817X"}, "institutions": [{"id": "https://openalex.org/I95457486", "display_name": "University of California, Berkeley", "ror": "https://ror.org/01an7q238", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I95457486"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Michael I. Jordan", "raw_affiliation_strings": ["Department of Electrical Engineering and Computer Sciences and Department of Statistics, University of California, Berkeley, CA, 94720, USA", "Department of Electrical Engineering and Computer Sciences and Department of Statistics, University of California, Berkeley, CA 94720, USA. jordan@cs.berkeley.edu"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Department of Electrical Engineering and Computer Sciences and Department of Statistics, University of California, Berkeley, CA, 94720, USA", "institution_ids": ["https://openalex.org/I95457486"]}, {"raw_affiliation_string": "Department of Electrical Engineering and Computer Sciences and Department of Statistics, University of California, Berkeley, CA 94720, USA. jordan@cs.berkeley.edu", "institution_ids": ["https://openalex.org/I95457486"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5010820865", "display_name": "Zoubin Ghahramani", "orcid": "https://orcid.org/0000-0002-7464-6475"}, "institutions": [{"id": "https://openalex.org/I4405268824", "display_name": "Gatsby Computational Neuroscience Unit", "ror": "https://ror.org/0269epf40", "country_code": "GB", "type": "facility", "lineage": ["https://openalex.org/I124357947", "https://openalex.org/I4405268824", "https://openalex.org/I45129253"]}, {"id": "https://openalex.org/I45129253", "display_name": "University College London", "ror": "https://ror.org/02jx3x895", "country_code": "GB", "type": "education", "lineage": ["https://openalex.org/I124357947", "https://openalex.org/I45129253"]}], "countries": ["GB"], "is_corresponding": false, "raw_author_name": "Zoubin Ghahramani", "raw_affiliation_strings": ["Gatsby Computational Neuroscience Unit, University College, London, WC1N 3AR, UK", "Gatsby Computational Neuroscience Unit, University College London WC1N 3AR, UK. zoubin@gatsby.ucl.ac.uk#TAB#"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Gatsby Computational Neuroscience Unit, University College, London, WC1N 3AR, UK", "institution_ids": ["https://openalex.org/I4405268824", "https://openalex.org/I45129253"]}, {"raw_affiliation_string": "Gatsby Computational Neuroscience Unit, University College London WC1N 3AR, UK. zoubin@gatsby.ucl.ac.uk#TAB#", "institution_ids": ["https://openalex.org/I4405268824", "https://openalex.org/I45129253"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5048915657", "display_name": "Tommi Jaakkola", "orcid": "https://orcid.org/0000-0002-2199-0379"}, "institutions": [{"id": "https://openalex.org/I63966007", "display_name": "Massachusetts Institute of Technology", "ror": "https://ror.org/042nb2s44", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I63966007"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Tommi S. Jaakkola", "raw_affiliation_strings": ["Artificial Intelligence Laboratory, MIT, Cambridge, MA, 02139, USA", "Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA. tommi@ai.mit.edu"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Artificial Intelligence Laboratory, MIT, Cambridge, MA, 02139, USA", "institution_ids": []}, {"raw_affiliation_string": "Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA. tommi@ai.mit.edu", "institution_ids": ["https://openalex.org/I63966007"]}]}, {"author_position": "last", "author": {"id": "https://openalex.org/A5103354854", "display_name": "Lawrence K. Saul", "orcid": null}, "institutions": [{"id": "https://openalex.org/I1283103587", "display_name": "AT&T (United States)", "ror": "https://ror.org/02bbd5539", "country_code": "US", "type": "company", "lineage": ["https://openalex.org/I1283103587"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Lawrence K. Saul", "raw_affiliation_strings": ["AT&T Labs\u2013Research, Florham Park, NJ, 07932, USA", "AT&T Labs\u2013Research, Florham Park, NJ 07932, USA. lsaul@research.att.edu"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "AT&T Labs\u2013Research, Florham Park, NJ, 07932, USA", "institution_ids": ["https://openalex.org/I1283103587"]}, {"raw_affiliation_string": "AT&T Labs\u2013Research, Florham Park, NJ 07932, USA. lsaul@research.att.edu", "institution_ids": ["https://openalex.org/I1283103587"]}]}], "institutions": [], "countries_distinct_count": 2, "institutions_distinct_count": 5, "corresponding_author_ids": [], "corresponding_institution_ids": [], "apc_list": {"value": 2990, "currency": "USD", "value_usd": 2990}, "apc_paid": null, "fwci": 52.9138, "has_fulltext": true, "cited_by_count": 3789, "citation_normalized_percentile": {"value": 0.99902429, "is_in_top_1_percent": true, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 99, "max": 100}, "biblio": {"volume": "37", "issue": "2", "first_page": "183", "last_page": "233"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T11303", "display_name": "Bayesian Modeling and Causal Inference", "score": 0.9998999834060669, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T11303", "display_name": "Bayesian Modeling and Causal Inference", "score": 0.9998999834060669, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T11901", "display_name": "Bayesian Methods and Mixture Models", "score": 0.992900013923645, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T12814", "display_name": "Gaussian Processes and Bayesian Inference", "score": 0.9889000058174133, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/graphical-model", "display_name": "Graphical model", "score": 0.8692572116851807}, {"id": "https://openalex.org/keywords/inference", "display_name": "Inference", "score": 0.597703754901886}, {"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.5496887564659119}, {"id": "https://openalex.org/keywords/bayesian-inference", "display_name": "Bayesian inference", "score": 0.4804815351963043}, {"id": "https://openalex.org/keywords/approximate-inference", "display_name": "Approximate inference", "score": 0.4630226492881775}, {"id": "https://openalex.org/keywords/algorithm", "display_name": "Algorithm", "score": 0.4484100043773651}, {"id": "https://openalex.org/keywords/bayesian-network", "display_name": "Bayesian network", "score": 0.42421048879623413}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.4189271926879883}, {"id": "https://openalex.org/keywords/theoretical-computer-science", "display_name": "Theoretical computer science", "score": 0.4052138030529022}, {"id": "https://openalex.org/keywords/mathematics", "display_name": "Mathematics", "score": 0.36878702044487}, {"id": "https://openalex.org/keywords/bayesian-probability", "display_name": "Bayesian probability", "score": 0.2710074782371521}], "concepts": [{"id": "https://openalex.org/C155846161", "wikidata": "https://www.wikidata.org/wiki/Q1143367", "display_name": "Graphical model", "level": 2, "score": 0.8692572116851807}, {"id": "https://openalex.org/C2776214188", "wikidata": "https://www.wikidata.org/wiki/Q408386", "display_name": "Inference", "level": 2, "score": 0.597703754901886}, {"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.5496887564659119}, {"id": "https://openalex.org/C160234255", "wikidata": "https://www.wikidata.org/wiki/Q812535", "display_name": "Bayesian inference", "level": 3, "score": 0.4804815351963043}, {"id": "https://openalex.org/C2777472644", "wikidata": "https://www.wikidata.org/wiki/Q16968992", "display_name": "Approximate inference", "level": 3, "score": 0.4630226492881775}, {"id": "https://openalex.org/C11413529", "wikidata": "https://www.wikidata.org/wiki/Q8366", "display_name": "Algorithm", "level": 1, "score": 0.4484100043773651}, {"id": "https://openalex.org/C33724603", "wikidata": "https://www.wikidata.org/wiki/Q812540", "display_name": "Bayesian network", "level": 2, "score": 0.42421048879623413}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.4189271926879883}, {"id": "https://openalex.org/C80444323", "wikidata": "https://www.wikidata.org/wiki/Q2878974", "display_name": "Theoretical computer science", "level": 1, "score": 0.4052138030529022}, {"id": "https://openalex.org/C33923547", "wikidata": "https://www.wikidata.org/wiki/Q395", "display_name": "Mathematics", "level": 0, "score": 0.36878702044487}, {"id": "https://openalex.org/C107673813", "wikidata": "https://www.wikidata.org/wiki/Q812534", "display_name": "Bayesian probability", "level": 2, "score": 0.2710074782371521}], "mesh": [], "locations_count": 1, "locations": [{"id": "doi:10.1023/a:1007665907178", "is_oa": true, "landing_page_url": "https://doi.org/10.1023/a:1007665907178", "pdf_url": "https://link.springer.com/content/pdf/10.1023/A:1007665907178.pdf", "source": {"id": "https://openalex.org/S62148650", "display_name": "Machine Learning", "issn_l": "0885-6125", "issn": ["0885-6125", "1573-0565"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310319900", "host_organization_name": "Springer Science+Business Media", "host_organization_lineage": ["https://openalex.org/P4310319900", "https://openalex.org/P4310319965"], "host_organization_lineage_names": ["Springer Science+Business Media", "Springer Nature"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Machine Learning", "raw_type": "journal-article"}], "best_oa_location": {"id": "doi:10.1023/a:1007665907178", "is_oa": true, "landing_page_url": "https://doi.org/10.1023/a:1007665907178", "pdf_url": "https://link.springer.com/content/pdf/10.1023/A:1007665907178.pdf", "source": {"id": "https://openalex.org/S62148650", "display_name": "Machine Learning", "issn_l": "0885-6125", "issn": ["0885-6125", "1573-0565"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310319900", "host_organization_name": "Springer Science+Business Media", "host_organization_lineage": ["https://openalex.org/P4310319900", "https://openalex.org/P4310319965"], "host_organization_lineage_names": ["Springer Science+Business Media", "Springer Nature"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Machine Learning", "raw_type": "journal-article"}, "sustainable_development_goals": [], "awards": [], "funders": [], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W1516111018.pdf", "grobid_xml": "https://content.openalex.org/works/W1516111018.grobid-xml"}, "referenced_works_count": 95, "referenced_works": ["https://openalex.org/W32516901", "https://openalex.org/W156498718", "https://openalex.org/W170122133", "https://openalex.org/W195465510", "https://openalex.org/W1481229783", "https://openalex.org/W1489119587", "https://openalex.org/W1500256440", "https://openalex.org/W1510302714", "https://openalex.org/W1520426560", "https://openalex.org/W1520448186", "https://openalex.org/W1528056001", "https://openalex.org/W1547224907", "https://openalex.org/W1573186872", "https://openalex.org/W1578685895", "https://openalex.org/W1587990862", "https://openalex.org/W1591751678", "https://openalex.org/W1592590442", "https://openalex.org/W1615454278", "https://openalex.org/W1746680969", "https://openalex.org/W1790295154", "https://openalex.org/W1810424324", "https://openalex.org/W1821294298", "https://openalex.org/W1829360078", "https://openalex.org/W1919989817", "https://openalex.org/W1972748205", "https://openalex.org/W1993845689", "https://openalex.org/W1999321705", "https://openalex.org/W1999432334", "https://openalex.org/W2020294948", "https://openalex.org/W2026799324", "https://openalex.org/W2032818204", "https://openalex.org/W2044442377", "https://openalex.org/W2047229728", "https://openalex.org/W2049633694", "https://openalex.org/W2062156211", "https://openalex.org/W2075450508", "https://openalex.org/W2082206048", "https://openalex.org/W2083380015", "https://openalex.org/W2086699924", "https://openalex.org/W2090361527", "https://openalex.org/W2099111195", "https://openalex.org/W2104163628", "https://openalex.org/W2105658140", "https://openalex.org/W2109787716", "https://openalex.org/W2110553242", "https://openalex.org/W2112798704", "https://openalex.org/W2116723448", "https://openalex.org/W2120633557", "https://openalex.org/W2128023014", "https://openalex.org/W2129031807", "https://openalex.org/W2133231442", "https://openalex.org/W2141876475", "https://openalex.org/W2145211911", "https://openalex.org/W2145550984", "https://openalex.org/W2147496287", "https://openalex.org/W2159080219", "https://openalex.org/W2167794538", "https://openalex.org/W2171265988", "https://openalex.org/W2175714895", "https://openalex.org/W2291425271", "https://openalex.org/W2567948266", "https://openalex.org/W2725061391", "https://openalex.org/W2982720039", "https://openalex.org/W2991334544", "https://openalex.org/W3004333419", "https://openalex.org/W3022628558", "https://openalex.org/W3103862435", "https://openalex.org/W4211064163", "https://openalex.org/W4240522930", "https://openalex.org/W4245655784", "https://openalex.org/W4245741392", "https://openalex.org/W4253572625", "https://openalex.org/W4285719527", "https://openalex.org/W4295161868", "https://openalex.org/W4300522856", "https://openalex.org/W4301208911", "https://openalex.org/W4302036486", "https://openalex.org/W6630045802", "https://openalex.org/W6632924624", "https://openalex.org/W6634379994", "https://openalex.org/W6635213487", "https://openalex.org/W6636455871", "https://openalex.org/W6638241908", "https://openalex.org/W6640071715", "https://openalex.org/W6658613897", "https://openalex.org/W6669328752", "https://openalex.org/W6671141409", "https://openalex.org/W6674851815", "https://openalex.org/W6676203565", "https://openalex.org/W6681138013", "https://openalex.org/W6681631443", "https://openalex.org/W6684585450", "https://openalex.org/W6769814042", "https://openalex.org/W6831535640", "https://openalex.org/W7048738093"], "related_works": ["https://openalex.org/W3183113072", "https://openalex.org/W2187019487", "https://openalex.org/W1715419791", "https://openalex.org/W2776613281", "https://openalex.org/W643788828", "https://openalex.org/W2158940596", "https://openalex.org/W2070797946", "https://openalex.org/W1727198190", "https://openalex.org/W2963071676", "https://openalex.org/W4297826693"], "abstract_inverted_index": null, "counts_by_year": [{"year": 2026, "cited_by_count": 75}, {"year": 2025, "cited_by_count": 139}, {"year": 2024, "cited_by_count": 119}, {"year": 2023, "cited_by_count": 120}, {"year": 2022, "cited_by_count": 133}, {"year": 2021, "cited_by_count": 257}, {"year": 2020, "cited_by_count": 331}, {"year": 2019, "cited_by_count": 308}, {"year": 2018, "cited_by_count": 231}, {"year": 2017, "cited_by_count": 191}, {"year": 2016, "cited_by_count": 180}, {"year": 2015, "cited_by_count": 192}, {"year": 2014, "cited_by_count": 158}, {"year": 2013, "cited_by_count": 143}, {"year": 2012, "cited_by_count": 185}], "updated_date": "2026-07-28T07:46:37.118299", "created_date": "2016-06-24T00:00:00"}, {"id": "https://openalex.org/W189514790", "doi": null, "title": "Conditional Random Fields: An Introduction", "display_name": "Conditional Random Fields: An Introduction", "relevance_score": 504.16824, "publication_year": 2004, "publication_date": "2004-01-01", "ids": {"openalex": "https://openalex.org/W189514790", "mag": "189514790"}, "language": "en", "primary_location": {"id": "pmh:oai:repository.upenn.edu:cis_reports-1011", "is_oa": true, "landing_page_url": "https://repository.upenn.edu/cis_reports/22", "pdf_url": "https://repository.upenn.edu/cis_reports/22", "source": {"id": "https://openalex.org/S4306402083", "display_name": "ScholarlyCommons (University of Pennsylvania)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I79576946", "host_organization_name": "University of Pennsylvania", "host_organization_lineage": ["https://openalex.org/I79576946"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Technical Reports (CIS)", "raw_type": "text"}, "type": "article", "indexed_in": [], "open_access": {"is_oa": true, "oa_status": "green", "oa_url": "https://repository.upenn.edu/cis_reports/22", "any_repository_has_fulltext": true}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5046348432", "display_name": "Hanna Wallach", "orcid": "https://orcid.org/0000-0003-3395-7186"}, "institutions": [{"id": "https://openalex.org/I36788626", "display_name": "California University of Pennsylvania", "ror": "https://ror.org/01spssf70", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I36788626"]}, {"id": "https://openalex.org/I79576946", "display_name": "University of Pennsylvania", "ror": "https://ror.org/00b30xv10", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I79576946"]}], "countries": ["US"], "is_corresponding": true, "raw_author_name": "Hanna Wallach", "raw_affiliation_strings": ["#N#               * University of Pennsylvania"], "raw_orcid": "https://orcid.org/0000-0003-3395-7186", "affiliations": [{"raw_affiliation_string": "#N#               * University of Pennsylvania", "institution_ids": ["https://openalex.org/I36788626", "https://openalex.org/I79576946"]}]}], "institutions": [], "countries_distinct_count": 1, "institutions_distinct_count": 2, "corresponding_author_ids": ["https://openalex.org/A5046348432"], "corresponding_institution_ids": ["https://openalex.org/I36788626", "https://openalex.org/I79576946"], "apc_list": null, "apc_paid": null, "fwci": 11.2518, "has_fulltext": true, "cited_by_count": 300, "citation_normalized_percentile": {"value": 0.98112839, "is_in_top_1_percent": false, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 91, "max": 100}, "biblio": {"volume": null, "issue": null, "first_page": null, "last_page": null}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T11269", "display_name": "Algorithms and Data Compression", "score": 0.9986000061035156, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T11269", "display_name": "Algorithms and Data Compression", "score": 0.9986000061035156, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T12072", "display_name": "Machine Learning and Algorithms", "score": 0.9825999736785889, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T12002", "display_name": "Computability, Logic, AI Algorithms", "score": 0.9682000279426575, "subfield": {"id": "https://openalex.org/subfields/1703", "display_name": "Computational Theory and Mathematics"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/conditional-random-field", "display_name": "Conditional random field", "score": 0.4734760522842407}, {"id": "https://openalex.org/keywords/mathematics", "display_name": "Mathematics", "score": 0.3985314965248108}, {"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.3928414583206177}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.23190715909004211}], "concepts": [{"id": "https://openalex.org/C152565575", "wikidata": "https://www.wikidata.org/wiki/Q1124538", "display_name": "Conditional random field", "level": 2, "score": 0.4734760522842407}, {"id": "https://openalex.org/C33923547", "wikidata": "https://www.wikidata.org/wiki/Q395", "display_name": "Mathematics", "level": 0, "score": 0.3985314965248108}, {"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.3928414583206177}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.23190715909004211}], "mesh": [], "locations_count": 10, "locations": [{"id": "pmh:oai:repository.upenn.edu:cis_reports-1011", "is_oa": true, "landing_page_url": "https://repository.upenn.edu/cis_reports/22", "pdf_url": "https://repository.upenn.edu/cis_reports/22", "source": {"id": "https://openalex.org/S4306402083", "display_name": "ScholarlyCommons (University of Pennsylvania)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I79576946", "host_organization_name": "University of Pennsylvania", "host_organization_lineage": ["https://openalex.org/I79576946"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Technical Reports (CIS)", "raw_type": "text"}, {"id": "pmh:oai:works.bepress.com:hanna_wallach-1000", "is_oa": true, "landing_page_url": "https://works.bepress.com/hanna_wallach/1", "pdf_url": "https://works.bepress.com/hanna_wallach/1", "source": {"id": "https://openalex.org/S4306402240", "display_name": "ScholarWorks@UMassAmherst (University of Massachusetts Amherst)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I24603500", "host_organization_name": "University of Massachusetts Amherst", "host_organization_lineage": ["https://openalex.org/I24603500"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Hanna M. Wallach", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.124.6711", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.124.6711", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.inference.phy.cam.ac.uk/hmw26/papers/crf_intro.ps", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.133.3955", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.133.3955", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cis.upenn.edu/datamining/ReadingGroup/papers/crf_intro.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.138.4696", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.138.4696", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cs.iastate.edu/~honavar/Seminars/Fall04/crf_intro.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.336.4324", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.336.4324", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.menem.com/~ilya/wiki/images/d/d4/Wallach-04.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.64.436", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.64.436", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.inference.phy.cam.ac.uk/hmw26/papers/crf_intro.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.974.9030", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.974.9030", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://repository.upenn.edu/cgi/viewcontent.cgi?article%3D1011%26context%3Dcis_reports", "raw_type": "text"}, {"id": "pmh:oai:repository.upenn.edu:20.500.14332/7126", "is_oa": false, "landing_page_url": "https://repository.upenn.edu/handle/20.500.14332/7126", "pdf_url": null, "source": {"id": "https://openalex.org/S4306402083", "display_name": "ScholarlyCommons (University of Pennsylvania)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I79576946", "host_organization_name": "University of Pennsylvania", "host_organization_lineage": ["https://openalex.org/I79576946"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "published", "raw_type": "Report"}, {"id": "mag:189514790", "is_oa": false, "landing_page_url": "https://repository.upenn.edu/cgi/viewcontent.cgi?article=1011&context=cis_reports", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": null, "is_accepted": false, "is_published": null, "raw_source_name": null, "raw_type": null}], "best_oa_location": {"id": "pmh:oai:repository.upenn.edu:cis_reports-1011", "is_oa": true, "landing_page_url": "https://repository.upenn.edu/cis_reports/22", "pdf_url": "https://repository.upenn.edu/cis_reports/22", "source": {"id": "https://openalex.org/S4306402083", "display_name": "ScholarlyCommons (University of Pennsylvania)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I79576946", "host_organization_name": "University of Pennsylvania", "host_organization_lineage": ["https://openalex.org/I79576946"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Technical Reports (CIS)", "raw_type": "text"}, "sustainable_development_goals": [], "awards": [], "funders": [], "has_content": {"grobid_xml": false, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W189514790.pdf"}, "referenced_works_count": 19, "referenced_works": ["https://openalex.org/W203785280", "https://openalex.org/W1550597138", "https://openalex.org/W1560013842", "https://openalex.org/W1820938075", "https://openalex.org/W1934019294", "https://openalex.org/W1995875735", "https://openalex.org/W2001792610", "https://openalex.org/W2009570821", "https://openalex.org/W2032558547", "https://openalex.org/W2034797903", "https://openalex.org/W2096175520", "https://openalex.org/W2114521167", "https://openalex.org/W2125838338", "https://openalex.org/W2147880316", "https://openalex.org/W2156515921", "https://openalex.org/W2752885492", "https://openalex.org/W2911427979", "https://openalex.org/W2952123276", "https://openalex.org/W3145128584"], "related_works": ["https://openalex.org/W2147880316", "https://openalex.org/W2125838338", "https://openalex.org/W2156515921", "https://openalex.org/W1934019294", "https://openalex.org/W1766290689", "https://openalex.org/W2141099517", "https://openalex.org/W2139193890", "https://openalex.org/W2020278455", "https://openalex.org/W2114361266", "https://openalex.org/W2096765155", "https://openalex.org/W1574901103", "https://openalex.org/W2107005506", "https://openalex.org/W2096175520", "https://openalex.org/W2051434435", "https://openalex.org/W2158188757", "https://openalex.org/W2129999749", "https://openalex.org/W2064675550", "https://openalex.org/W1991133427", "https://openalex.org/W2163107094", "https://openalex.org/W2036516910"], "abstract_inverted_index": {"University": [0], "of": [1, 4], "Pennsylvania": [2], "Department": [3], "Computer": [5], "and": [6], "Information": [7], "Science": [8], "Technical": [9], "Report": [10], "No.": [11], "MS-CIS-04-21.": [12]}, "counts_by_year": [{"year": 2025, "cited_by_count": 1}, {"year": 2024, "cited_by_count": 2}, {"year": 2023, "cited_by_count": 16}, {"year": 2022, "cited_by_count": 15}, {"year": 2021, "cited_by_count": 13}, {"year": 2020, "cited_by_count": 12}, {"year": 2019, "cited_by_count": 13}, {"year": 2018, "cited_by_count": 12}, {"year": 2017, "cited_by_count": 13}, {"year": 2016, "cited_by_count": 7}, {"year": 2015, "cited_by_count": 15}, {"year": 2014, "cited_by_count": 20}, {"year": 2013, "cited_by_count": 26}, {"year": 2012, "cited_by_count": 36}], "updated_date": "2026-08-04T08:18:43.703281", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W2153959628", "doi": "https://doi.org/10.1609/aimag.v29i3.2157", "title": "Collective Classification in Network Data", "display_name": "Collective Classification in Network Data", "relevance_score": 504.05478, "publication_year": 2008, "publication_date": "2008-09-01", "ids": {"openalex": "https://openalex.org/W2153959628", "doi": "https://doi.org/10.1609/aimag.v29i3.2157", "mag": "2153959628"}, "language": "en", "primary_location": {"id": "doi:10.1609/aimag.v29i3.2157", "is_oa": true, "landing_page_url": "https://doi.org/10.1609/aimag.v29i3.2157", "pdf_url": "https://ojs.aaai.org/index.php/aimagazine/article/download/2157/2022", "source": {"id": "https://openalex.org/S163019073", "display_name": "AI Magazine", "issn_l": "0738-4602", "issn": ["0738-4602", "2371-9621"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310320058", "host_organization_name": "Association for the Advancement of Artificial Intelligence", "host_organization_lineage": ["https://openalex.org/P4310320058"], "host_organization_lineage_names": ["Association for the Advancement of Artificial Intelligence"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "AI Magazine", "raw_type": "journal-article"}, "type": "article", "indexed_in": ["crossref"], "open_access": {"is_oa": true, "oa_status": "bronze", "oa_url": "https://ojs.aaai.org/index.php/aimagazine/article/download/2157/2022", "any_repository_has_fulltext": false}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5105422045", "display_name": "Prithviraj Sen", "orcid": null}, "institutions": [{"id": "https://openalex.org/I66946132", "display_name": "University of Maryland, College Park", "ror": "https://ror.org/047s2c258", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I66946132"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Prithviraj Sen", "raw_affiliation_strings": ["University of Maryland"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Maryland", "institution_ids": ["https://openalex.org/I66946132"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5016455363", "display_name": "Galileo Namata", "orcid": null}, "institutions": [{"id": "https://openalex.org/I66946132", "display_name": "University of Maryland, College Park", "ror": "https://ror.org/047s2c258", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I66946132"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Galileo Namata", "raw_affiliation_strings": ["University of Maryland"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Maryland", "institution_ids": ["https://openalex.org/I66946132"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5038378351", "display_name": "Mustafa Bilgic", "orcid": "https://orcid.org/0000-0001-5123-9992"}, "institutions": [{"id": "https://openalex.org/I66946132", "display_name": "University of Maryland, College Park", "ror": "https://ror.org/047s2c258", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I66946132"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Mustafa Bilgic", "raw_affiliation_strings": ["University of Maryland"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Maryland", "institution_ids": ["https://openalex.org/I66946132"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5086169451", "display_name": "Lise Getoor", "orcid": null}, "institutions": [{"id": "https://openalex.org/I66946132", "display_name": "University of Maryland, College Park", "ror": "https://ror.org/047s2c258", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I66946132"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Lise Getoor", "raw_affiliation_strings": ["University of Maryland"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Maryland", "institution_ids": ["https://openalex.org/I66946132"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5055448715", "display_name": "Brian Gallagher", "orcid": "https://orcid.org/0000-0002-3262-6652"}, "institutions": [{"id": "https://openalex.org/I66946132", "display_name": "University of Maryland, College Park", "ror": "https://ror.org/047s2c258", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I66946132"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Brian Gallagher", "raw_affiliation_strings": ["University of Maryland"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Maryland", "institution_ids": ["https://openalex.org/I66946132"]}]}, {"author_position": "last", "author": {"id": "https://openalex.org/A5080731595", "display_name": "Tina Eliassi\u2010Rad", "orcid": "https://orcid.org/0000-0002-1892-1188"}, "institutions": [{"id": "https://openalex.org/I66946132", "display_name": "University of Maryland, College Park", "ror": "https://ror.org/047s2c258", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I66946132"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Tina Eliassi\u2010Rad", "raw_affiliation_strings": ["University of Maryland"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Maryland", "institution_ids": ["https://openalex.org/I66946132"]}]}], "institutions": [], "countries_distinct_count": 1, "institutions_distinct_count": 1, "corresponding_author_ids": [], "corresponding_institution_ids": ["https://openalex.org/I66946132"], "apc_list": {"value": 2400, "currency": "USD", "value_usd": 2400}, "apc_paid": null, "fwci": 29.7555, "has_fulltext": true, "cited_by_count": 3318, "citation_normalized_percentile": {"value": 0.9986318, "is_in_top_1_percent": true, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 99, "max": 100}, "biblio": {"volume": "29", "issue": "3", "first_page": "93", "last_page": "106"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10064", "display_name": "Complex Network Analysis Techniques", "score": 0.9986000061035156, "subfield": {"id": "https://openalex.org/subfields/3109", "display_name": "Statistical and Nonlinear Physics"}, "field": {"id": "https://openalex.org/fields/31", "display_name": "Physics and Astronomy"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10064", "display_name": "Complex Network Analysis Techniques", "score": 0.9986000061035156, "subfield": {"id": "https://openalex.org/subfields/3109", "display_name": "Statistical and Nonlinear Physics"}, "field": {"id": "https://openalex.org/fields/31", "display_name": "Physics and Astronomy"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T11273", "display_name": "Advanced Graph Neural Networks", "score": 0.9980999827384949, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10887", "display_name": "Bioinformatics and Genomic Networks", "score": 0.9937999844551086, "subfield": {"id": "https://openalex.org/subfields/1312", "display_name": "Molecular Biology"}, "field": {"id": "https://openalex.org/fields/13", "display_name": "Biochemistry, Genetics and Molecular Biology"}, "domain": {"id": "https://openalex.org/domains/1", "display_name": "Life Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.7650193572044373}, {"id": "https://openalex.org/keywords/hyperlink", "display_name": "Hyperlink", "score": 0.6757919788360596}, {"id": "https://openalex.org/keywords/hypertext", "display_name": "Hypertext", "score": 0.6066907644271851}, {"id": "https://openalex.org/keywords/inference", "display_name": "Inference", "score": 0.523329496383667}, {"id": "https://openalex.org/keywords/focus", "display_name": "Focus (optics)", "score": 0.5123189687728882}, {"id": "https://openalex.org/keywords/friendship", "display_name": "Friendship", "score": 0.4914346933364868}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.4516136944293976}, {"id": "https://openalex.org/keywords/data-science", "display_name": "Data science", "score": 0.4363569915294647}, {"id": "https://openalex.org/keywords/world-wide-web", "display_name": "World Wide Web", "score": 0.43423283100128174}, {"id": "https://openalex.org/keywords/machine-learning", "display_name": "Machine learning", "score": 0.42560991644859314}, {"id": "https://openalex.org/keywords/web-page", "display_name": "Web page", "score": 0.1636728048324585}], "concepts": [{"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.7650193572044373}, {"id": "https://openalex.org/C30088001", "wikidata": "https://www.wikidata.org/wiki/Q102014", "display_name": "Hyperlink", "level": 3, "score": 0.6757919788360596}, {"id": "https://openalex.org/C162215914", "wikidata": "https://www.wikidata.org/wiki/Q93241", "display_name": "Hypertext", "level": 2, "score": 0.6066907644271851}, {"id": "https://openalex.org/C2776214188", "wikidata": "https://www.wikidata.org/wiki/Q408386", "display_name": "Inference", "level": 2, "score": 0.523329496383667}, {"id": "https://openalex.org/C192209626", "wikidata": "https://www.wikidata.org/wiki/Q190909", "display_name": "Focus (optics)", "level": 2, "score": 0.5123189687728882}, {"id": "https://openalex.org/C2778736484", "wikidata": "https://www.wikidata.org/wiki/Q491", "display_name": "Friendship", "level": 2, "score": 0.4914346933364868}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.4516136944293976}, {"id": "https://openalex.org/C2522767166", "wikidata": "https://www.wikidata.org/wiki/Q2374463", "display_name": "Data science", "level": 1, "score": 0.4363569915294647}, {"id": "https://openalex.org/C136764020", "wikidata": "https://www.wikidata.org/wiki/Q466", "display_name": "World Wide Web", "level": 1, "score": 0.43423283100128174}, {"id": "https://openalex.org/C119857082", "wikidata": "https://www.wikidata.org/wiki/Q2539", "display_name": "Machine learning", "level": 1, "score": 0.42560991644859314}, {"id": "https://openalex.org/C21959979", "wikidata": "https://www.wikidata.org/wiki/Q36774", "display_name": "Web page", "level": 2, "score": 0.1636728048324585}, {"id": "https://openalex.org/C15744967", "wikidata": "https://www.wikidata.org/wiki/Q9418", "display_name": "Psychology", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C121332964", "wikidata": "https://www.wikidata.org/wiki/Q413", "display_name": "Physics", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C77805123", "wikidata": "https://www.wikidata.org/wiki/Q161272", "display_name": "Social psychology", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C120665830", "wikidata": "https://www.wikidata.org/wiki/Q14620", "display_name": "Optics", "level": 1, "score": 0.0}], "mesh": [], "locations_count": 4, "locations": [{"id": "doi:10.1609/aimag.v29i3.2157", "is_oa": true, "landing_page_url": "https://doi.org/10.1609/aimag.v29i3.2157", "pdf_url": "https://ojs.aaai.org/index.php/aimagazine/article/download/2157/2022", "source": {"id": "https://openalex.org/S163019073", "display_name": "AI Magazine", "issn_l": "0738-4602", "issn": ["0738-4602", "2371-9621"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310320058", "host_organization_name": "Association for the Advancement of Artificial Intelligence", "host_organization_lineage": ["https://openalex.org/P4310320058"], "host_organization_lineage_names": ["Association for the Advancement of Artificial Intelligence"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "AI Magazine", "raw_type": "journal-article"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.188.906", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.188.906", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cs.umd.edu/%7Embilgic/pdfs/umtr08.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.385.5338", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.385.5338", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://eliassi.org/papers/sen-aimag-fall08.pdf", "raw_type": "text"}, {"id": "pmh:oai:drum.lib.umd.edu:1903/7546", "is_oa": false, "landing_page_url": "http://hdl.handle.net/1903/7546", "pdf_url": null, "source": {"id": "https://openalex.org/S4306401518", "display_name": "University Libraries (University of Maryland)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I66946132", "host_organization_name": "University of Maryland, College Park", "host_organization_lineage": ["https://openalex.org/I66946132"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": null, "raw_type": "Technical Report"}], "best_oa_location": {"id": "doi:10.1609/aimag.v29i3.2157", "is_oa": true, "landing_page_url": "https://doi.org/10.1609/aimag.v29i3.2157", "pdf_url": "https://ojs.aaai.org/index.php/aimagazine/article/download/2157/2022", "source": {"id": "https://openalex.org/S163019073", "display_name": "AI Magazine", "issn_l": "0738-4602", "issn": ["0738-4602", "2371-9621"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310320058", "host_organization_name": "Association for the Advancement of Artificial Intelligence", "host_organization_lineage": ["https://openalex.org/P4310320058"], "host_organization_lineage_names": ["Association for the Advancement of Artificial Intelligence"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "AI Magazine", "raw_type": "journal-article"}, "sustainable_development_goals": [], "awards": [{"id": "https://openalex.org/G1088636562", "display_name": null, "funder_award_id": "DE-AC52-07-NA27344", "funder_id": "https://openalex.org/F4320306076", "funder_display_name": "National Science Foundation"}, {"id": "https://openalex.org/G1356433355", "display_name": null, "funder_award_id": "DE\u2010AC5207NA27344", "funder_id": "https://openalex.org/F4320338286", "funder_display_name": "Lawrence Livermore National Laboratory"}, {"id": "https://openalex.org/G14554683", "display_name": null, "funder_award_id": "DEAC5207NA27344", "funder_id": "https://openalex.org/F4320306084", "funder_display_name": "U.S. Department of Energy"}, {"id": "https://openalex.org/G2145270357", "display_name": null, "funder_award_id": "AC52\u201007NA27344", "funder_id": "https://openalex.org/F4320306084", "funder_display_name": "U.S. Department of Energy"}, {"id": "https://openalex.org/G3190050964", "display_name": "Link Mining and Discovery", "funder_award_id": "0308030", "funder_id": "https://openalex.org/F4320306076", "funder_display_name": "National Science Foundation"}, {"id": "https://openalex.org/G4343739756", "display_name": null, "funder_award_id": "Contract DE-AC52-07NA27344", "funder_id": "https://openalex.org/F4320338286", "funder_display_name": "Lawrence Livermore National Laboratory"}, {"id": "https://openalex.org/G69709960", "display_name": null, "funder_award_id": "Contract DE-AC52-07NA27344", "funder_id": "https://openalex.org/F4320306084", "funder_display_name": "U.S. Department of Energy"}, {"id": "https://openalex.org/G991281326", "display_name": null, "funder_award_id": "AC52-07NA27344", "funder_id": "https://openalex.org/F4320338286", "funder_display_name": "Lawrence Livermore National Laboratory"}], "funders": [{"id": "https://openalex.org/F4320306076", "display_name": "National Science Foundation", "ror": "https://ror.org/021nxhr62"}, {"id": "https://openalex.org/F4320306084", "display_name": "U.S. Department of Energy", "ror": "https://ror.org/01bj3aw27"}, {"id": "https://openalex.org/F4320338286", "display_name": "Lawrence Livermore National Laboratory", "ror": "https://ror.org/041nk4h53"}], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2153959628.pdf", "grobid_xml": "https://content.openalex.org/works/W2153959628.grobid-xml"}, "referenced_works_count": 74, "referenced_works": ["https://openalex.org/W18554110", "https://openalex.org/W122594028", "https://openalex.org/W204750116", "https://openalex.org/W595549847", "https://openalex.org/W1482260847", "https://openalex.org/W1488357069", "https://openalex.org/W1496450597", "https://openalex.org/W1498273559", "https://openalex.org/W1510372738", "https://openalex.org/W1516111018", "https://openalex.org/W1524037464", "https://openalex.org/W1528012351", "https://openalex.org/W1545331097", "https://openalex.org/W1554544485", "https://openalex.org/W1605615716", "https://openalex.org/W1666347389", "https://openalex.org/W1785889609", "https://openalex.org/W1800493452", "https://openalex.org/W1852143573", "https://openalex.org/W1908728294", "https://openalex.org/W1934021597", "https://openalex.org/W1949708275", "https://openalex.org/W1977970897", "https://openalex.org/W2016044775", "https://openalex.org/W2020999234", "https://openalex.org/W2047408445", "https://openalex.org/W2049073556", "https://openalex.org/W2076008912", "https://openalex.org/W2078029048", "https://openalex.org/W2079914085", "https://openalex.org/W2095688344", "https://openalex.org/W2097826433", "https://openalex.org/W2098678088", "https://openalex.org/W2100034662", "https://openalex.org/W2101705355", "https://openalex.org/W2105644991", "https://openalex.org/W2107792892", "https://openalex.org/W2108346334", "https://openalex.org/W2108619558", "https://openalex.org/W2108817075", "https://openalex.org/W2115703234", "https://openalex.org/W2121250409", "https://openalex.org/W2123827533", "https://openalex.org/W2124637492", "https://openalex.org/W2126185296", "https://openalex.org/W2127058089", "https://openalex.org/W2127345773", "https://openalex.org/W2129031807", "https://openalex.org/W2130354913", "https://openalex.org/W2130416410", "https://openalex.org/W2134700719", "https://openalex.org/W2137253512", "https://openalex.org/W2137813581", "https://openalex.org/W2138798845", "https://openalex.org/W2141876475", "https://openalex.org/W2143516773", "https://openalex.org/W2147880316", "https://openalex.org/W2162630660", "https://openalex.org/W2164179075", "https://openalex.org/W2167044614", "https://openalex.org/W2168190036", "https://openalex.org/W2168772685", "https://openalex.org/W2169415915", "https://openalex.org/W2185735208", "https://openalex.org/W2523494790", "https://openalex.org/W2540462820", "https://openalex.org/W2913318000", "https://openalex.org/W2962735828", "https://openalex.org/W2987657883", "https://openalex.org/W2999905431", "https://openalex.org/W4231458249", "https://openalex.org/W4240278298", "https://openalex.org/W4285719527", "https://openalex.org/W6675204935"], "related_works": ["https://openalex.org/W2988234774", "https://openalex.org/W3158912095", "https://openalex.org/W392148851", "https://openalex.org/W2074301807", "https://openalex.org/W2051102072", "https://openalex.org/W2275637146", "https://openalex.org/W2403512859", "https://openalex.org/W1988192941", "https://openalex.org/W1593066723", "https://openalex.org/W3126855651"], "abstract_inverted_index": {"Many": [0], "real\u2010world": [1, 104], "applications": [2], "produce": [3], "networked": [4, 94], "data": [5, 95], "such": [6, 58], "as": [7, 19, 36], "the": [8, 79, 86], "worldwide": [9], "web": [10], "(hypertext": [11], "documents": [12], "connected": [13, 21, 28], "through": [14, 29], "hyperlinks),": [15], "social": [16], "networks": [17, 26, 34], "(such": [18, 35], "people": [20], "by": [22], "friendship": [23], "links),": [24, 31], "communication": [25, 30], "(computers": [27], "and": [32, 73, 96, 103], "biological": [33], "protein": [37], "interaction": [38], "networks).": [39], "A": [40], "recent": [41], "focus": [42], "in": [43, 57], "machine\u2010learning": [44, 51], "research": [45, 72], "has": [46, 76], "been": [47], "to": [48, 54, 68], "extend": [49], "traditional": [50], "classification": [52], "techniques": [53], "classify": [55], "nodes": [56], "networks.": [59], "In": [60], "this": [61, 69], "article,": [62], "we": [63], "provide": [64], "a": [65], "brief": [66], "introduction": [67], "area": [70], "of": [71, 85], "how": [74], "it": [75], "progressed": [77], "during": [78], "past": [80], "decade.": [81], "We": [82], "introduce": [83], "four": [84], "most": [87], "widely": [88], "used": [89], "inference": [90], "algorithms": [91], "for": [92], "classifying": [93], "empirically": [97], "compare": [98], "them": [99], "on": [100], "both": [101], "synthetic": [102], "data.": [105]}, "counts_by_year": [{"year": 2026, "cited_by_count": 116}, {"year": 2025, "cited_by_count": 401}, {"year": 2024, "cited_by_count": 403}, {"year": 2023, "cited_by_count": 400}, {"year": 2022, "cited_by_count": 340}, {"year": 2021, "cited_by_count": 482}, {"year": 2020, "cited_by_count": 363}, {"year": 2019, "cited_by_count": 235}, {"year": 2018, "cited_by_count": 104}, {"year": 2017, "cited_by_count": 65}, {"year": 2016, "cited_by_count": 52}, {"year": 2015, "cited_by_count": 67}, {"year": 2014, "cited_by_count": 63}, {"year": 2013, "cited_by_count": 58}, {"year": 2012, "cited_by_count": 51}], "updated_date": "2026-08-01T09:00:35.917206", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W2114361266", "doi": "https://doi.org/10.3115/1567594.1567618", "title": "Biomedical named entity recognition using conditional random fields and rich feature sets", "display_name": "Biomedical named entity recognition using conditional random fields and rich feature sets", "relevance_score": 496.45718, "publication_year": 2004, "publication_date": "2004-01-01", "ids": {"openalex": "https://openalex.org/W2114361266", "doi": "https://doi.org/10.3115/1567594.1567618", "mag": "2114361266"}, "language": "en", "primary_location": {"id": "doi:10.3115/1567594.1567618", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1567594.1567618", "pdf_url": "https://dl.acm.org/doi/pdf/10.5555/1567594.1567618", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications - JNLPBA '04", "raw_type": "proceedings-article"}, "type": "conference-paper", "indexed_in": ["crossref"], "open_access": {"is_oa": true, "oa_status": "gold", "oa_url": "https://dl.acm.org/doi/pdf/10.5555/1567594.1567618", "any_repository_has_fulltext": null}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5028683722", "display_name": "Burr Settles", "orcid": null}, "institutions": [{"id": "https://openalex.org/I135310074", "display_name": "University of Wisconsin\u2013Madison", "ror": "https://ror.org/01y2jtd41", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I135310074"]}], "countries": ["US"], "is_corresponding": true, "raw_author_name": "Burr Settles", "raw_affiliation_strings": ["University of Wisconsin-Madison, Madison, WI", "University of Wisconsin, Madison Madison, WI"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Wisconsin-Madison, Madison, WI", "institution_ids": ["https://openalex.org/I135310074"]}, {"raw_affiliation_string": "University of Wisconsin, Madison Madison, WI", "institution_ids": ["https://openalex.org/I135310074"]}]}], "institutions": [], "countries_distinct_count": 1, "institutions_distinct_count": 1, "corresponding_author_ids": ["https://openalex.org/A5028683722"], "corresponding_institution_ids": ["https://openalex.org/I135310074"], "apc_list": null, "apc_paid": null, "fwci": 12.1242, "has_fulltext": true, "cited_by_count": 527, "citation_normalized_percentile": {"value": 0.99234075, "is_in_top_1_percent": true, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 99, "max": 100}, "biblio": {"volume": null, "issue": null, "first_page": "104", "last_page": "104"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9998999834060669, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9998999834060669, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 0.9998000264167786, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T11710", "display_name": "Biomedical Text Mining and Ontologies", "score": 0.9994000196456909, "subfield": {"id": "https://openalex.org/subfields/1312", "display_name": "Molecular Biology"}, "field": {"id": "https://openalex.org/fields/13", "display_name": "Biochemistry, Genetics and Molecular Biology"}, "domain": {"id": "https://openalex.org/domains/1", "display_name": "Life Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/conditional-random-field", "display_name": "Conditional random field", "score": 0.8503983616828918}, {"id": "https://openalex.org/keywords/named-entity-recognition", "display_name": "Named-entity recognition", "score": 0.8375948071479797}, {"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.7984488606452942}, {"id": "https://openalex.org/keywords/feature", "display_name": "Feature (linguistics)", "score": 0.670075535774231}, {"id": "https://openalex.org/keywords/task", "display_name": "Task (project management)", "score": 0.6676212549209595}, {"id": "https://openalex.org/keywords/natural-language-processing", "display_name": "Natural language processing", "score": 0.6610902547836304}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.6144940853118896}, {"id": "https://openalex.org/keywords/named-entity", "display_name": "Named entity", "score": 0.5763100385665894}, {"id": "https://openalex.org/keywords/entity-linking", "display_name": "Entity linking", "score": 0.4789424538612366}, {"id": "https://openalex.org/keywords/natural-language", "display_name": "Natural language", "score": 0.45365822315216064}, {"id": "https://openalex.org/keywords/information-retrieval", "display_name": "Information retrieval", "score": 0.3847983777523041}, {"id": "https://openalex.org/keywords/knowledge-base", "display_name": "Knowledge base", "score": 0.1672995686531067}, {"id": "https://openalex.org/keywords/linguistics", "display_name": "Linguistics", "score": 0.1357181966304779}], "concepts": [{"id": "https://openalex.org/C152565575", "wikidata": "https://www.wikidata.org/wiki/Q1124538", "display_name": "Conditional random field", "level": 2, "score": 0.8503983616828918}, {"id": "https://openalex.org/C2779135771", "wikidata": "https://www.wikidata.org/wiki/Q403574", "display_name": "Named-entity recognition", "level": 3, "score": 0.8375948071479797}, {"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.7984488606452942}, {"id": "https://openalex.org/C2776401178", "wikidata": "https://www.wikidata.org/wiki/Q12050496", "display_name": "Feature (linguistics)", "level": 2, "score": 0.670075535774231}, {"id": "https://openalex.org/C2780451532", "wikidata": "https://www.wikidata.org/wiki/Q759676", "display_name": "Task (project management)", "level": 2, "score": 0.6676212549209595}, {"id": "https://openalex.org/C204321447", "wikidata": "https://www.wikidata.org/wiki/Q30642", "display_name": "Natural language processing", "level": 1, "score": 0.6610902547836304}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.6144940853118896}, {"id": "https://openalex.org/C2777889803", "wikidata": "https://www.wikidata.org/wiki/Q25047676", "display_name": "Named entity", "level": 2, "score": 0.5763100385665894}, {"id": "https://openalex.org/C96711827", "wikidata": "https://www.wikidata.org/wiki/Q17012245", "display_name": "Entity linking", "level": 3, "score": 0.4789424538612366}, {"id": "https://openalex.org/C195324797", "wikidata": "https://www.wikidata.org/wiki/Q33742", "display_name": "Natural language", "level": 2, "score": 0.45365822315216064}, {"id": "https://openalex.org/C23123220", "wikidata": "https://www.wikidata.org/wiki/Q816826", "display_name": "Information retrieval", "level": 1, "score": 0.3847983777523041}, {"id": "https://openalex.org/C4554734", "wikidata": "https://www.wikidata.org/wiki/Q593744", "display_name": "Knowledge base", "level": 2, "score": 0.1672995686531067}, {"id": "https://openalex.org/C41895202", "wikidata": "https://www.wikidata.org/wiki/Q8162", "display_name": "Linguistics", "level": 1, "score": 0.1357181966304779}, {"id": "https://openalex.org/C187736073", "wikidata": "https://www.wikidata.org/wiki/Q2920921", "display_name": "Management", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C138885662", "wikidata": "https://www.wikidata.org/wiki/Q5891", "display_name": "Philosophy", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C162324750", "wikidata": "https://www.wikidata.org/wiki/Q8134", "display_name": "Economics", "level": 0, "score": 0.0}], "mesh": [], "locations_count": 3, "locations": [{"id": "doi:10.3115/1567594.1567618", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1567594.1567618", "pdf_url": "https://dl.acm.org/doi/pdf/10.5555/1567594.1567618", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications - JNLPBA '04", "raw_type": "proceedings-article"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.112.7693", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.112.7693", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cs.wisc.edu/~bsettles/pub/bsettles-nlpba04.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.154.2547", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.2547", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.aclweb.org/anthology-new/W/W04/W04-1221.pdf", "raw_type": "text"}], "best_oa_location": {"id": "doi:10.3115/1567594.1567618", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1567594.1567618", "pdf_url": "https://dl.acm.org/doi/pdf/10.5555/1567594.1567618", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications - JNLPBA '04", "raw_type": "proceedings-article"}, "sustainable_development_goals": [{"display_name": "Quality Education", "score": 0.8399999737739563, "id": "https://metadata.un.org/sdg/4"}], "awards": [{"id": "https://openalex.org/G3308204928", "display_name": "Computation and Informatics in Biology and Medicine", "funder_award_id": "5t15lm007359-22", "funder_id": "https://openalex.org/F4320332161", "funder_display_name": "National Institutes of Health"}], "funders": [{"id": "https://openalex.org/F4320332161", "display_name": "National Institutes of Health", "ror": "https://ror.org/01cwqze88"}], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2114361266.pdf", "grobid_xml": "https://content.openalex.org/works/W2114361266.grobid-xml"}, "referenced_works_count": 6, "referenced_works": ["https://openalex.org/W2130260860", "https://openalex.org/W2141099517", "https://openalex.org/W2144087279", "https://openalex.org/W2147880316", "https://openalex.org/W2151296343", "https://openalex.org/W2156515921"], "related_works": ["https://openalex.org/W2186562580", "https://openalex.org/W2032007337", "https://openalex.org/W4255258373", "https://openalex.org/W2593907245", "https://openalex.org/W2155874911", "https://openalex.org/W3000685722", "https://openalex.org/W2614126974", "https://openalex.org/W1884363728", "https://openalex.org/W1964783010", "https://openalex.org/W11196620"], "abstract_inverted_index": {"As": [0], "the": [1, 7], "wealth": [2], "of": [3, 9, 40, 53, 62], "biomedical": [4], "knowledge": [5], "in": [6, 25, 45], "form": [8], "literature": [10], "increases,": [11], "there": [12], "is": [13, 55], "a": [14], "rising": [15], "need": [16], "for": [17, 60], "effective": [18], "natural": [19], "language": [20], "processing": [21], "tools": [22], "to": [23, 50], "assist": [24], "organizing,": [26], "curating,": [27], "and": [28, 43], "retrieving": [29], "this": [30], "information.": [31], "To": [32], "that": [33, 48], "end,": [34], "named": [35], "entity": [36], "recognition": [37], "(the": [38], "task": [39], "identifying": [41], "words": [42], "phrases": [44], "free": [46], "text": [47], "belong": [49], "certain": [51], "classes": [52], "interest)": [54], "an": [56], "important": [57], "first": [58], "step": [59], "many": [61], "these": [63], "larger": [64], "information": [65], "management": [66], "goals.": [67]}, "counts_by_year": [{"year": 2026, "cited_by_count": 5}, {"year": 2025, "cited_by_count": 12}, {"year": 2024, "cited_by_count": 16}, {"year": 2023, "cited_by_count": 29}, {"year": 2022, "cited_by_count": 20}, {"year": 2021, "cited_by_count": 26}, {"year": 2020, "cited_by_count": 31}, {"year": 2019, "cited_by_count": 34}, {"year": 2018, "cited_by_count": 16}, {"year": 2017, "cited_by_count": 32}, {"year": 2016, "cited_by_count": 26}, {"year": 2015, "cited_by_count": 23}, {"year": 2014, "cited_by_count": 29}, {"year": 2013, "cited_by_count": 28}, {"year": 2012, "cited_by_count": 36}], "updated_date": "2026-08-06T08:24:18.245995", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W2136140395", "doi": "https://doi.org/10.3115/1220575.1220620", "title": "Identifying sources of opinions with conditional random fields and extraction patterns", "display_name": "Identifying sources of opinions with conditional random fields and extraction patterns", "relevance_score": 495.26538, "publication_year": 2005, "publication_date": "2005-01-01", "ids": {"openalex": "https://openalex.org/W2136140395", "doi": "https://doi.org/10.3115/1220575.1220620", "mag": "2136140395"}, "language": "en", "primary_location": {"id": "doi:10.3115/1220575.1220620", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1220575.1220620", "pdf_url": "https://dl.acm.org/doi/pdf/10.3115/1220575.1220620", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing - HLT '05", "raw_type": "proceedings-article"}, "type": "conference-paper", "indexed_in": ["crossref"], "open_access": {"is_oa": true, "oa_status": "gold", "oa_url": "https://dl.acm.org/doi/pdf/10.3115/1220575.1220620", "any_repository_has_fulltext": null}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5102992157", "display_name": "Yejin Choi", "orcid": "https://orcid.org/0000-0003-3032-5378"}, "institutions": [{"id": "https://openalex.org/I205783295", "display_name": "Cornell University", "ror": "https://ror.org/05bnh6r87", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I205783295"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Yejin Choi", "raw_affiliation_strings": ["Cornell University, Ithaca, NY", "Cornell University (Ithaca, NY);"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Cornell University, Ithaca, NY", "institution_ids": ["https://openalex.org/I205783295"]}, {"raw_affiliation_string": "Cornell University (Ithaca, NY);", "institution_ids": ["https://openalex.org/I205783295"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5070511738", "display_name": "Claire Cardie", "orcid": "https://orcid.org/0000-0002-2061-6094"}, "institutions": [{"id": "https://openalex.org/I205783295", "display_name": "Cornell University", "ror": "https://ror.org/05bnh6r87", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I205783295"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Claire Cardie", "raw_affiliation_strings": ["Cornell University, Ithaca, NY", "Cornell University (Ithaca, NY);"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Cornell University, Ithaca, NY", "institution_ids": ["https://openalex.org/I205783295"]}, {"raw_affiliation_string": "Cornell University (Ithaca, NY);", "institution_ids": ["https://openalex.org/I205783295"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5005791318", "display_name": "Ellen Riloff", "orcid": null}, "institutions": [{"id": "https://openalex.org/I223532165", "display_name": "University of Utah", "ror": "https://ror.org/03r0ha626", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I223532165"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Ellen Riloff", "raw_affiliation_strings": ["University of Utah, Salt Lake City, UT", "University of Utah; Salt Lake City; UT"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Utah, Salt Lake City, UT", "institution_ids": ["https://openalex.org/I223532165"]}, {"raw_affiliation_string": "University of Utah; Salt Lake City; UT", "institution_ids": ["https://openalex.org/I223532165"]}]}, {"author_position": "last", "author": {"id": "https://openalex.org/A5102909728", "display_name": "Siddharth Patwardhan", "orcid": "https://orcid.org/0000-0002-7355-355X"}, "institutions": [{"id": "https://openalex.org/I223532165", "display_name": "University of Utah", "ror": "https://ror.org/03r0ha626", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I223532165"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Siddharth Patwardhan", "raw_affiliation_strings": ["University of Utah, Salt Lake City, UT", "University of Utah; Salt Lake City; UT"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Utah, Salt Lake City, UT", "institution_ids": ["https://openalex.org/I223532165"]}, {"raw_affiliation_string": "University of Utah; Salt Lake City; UT", "institution_ids": ["https://openalex.org/I223532165"]}]}], "institutions": [], "countries_distinct_count": 1, "institutions_distinct_count": 2, "corresponding_author_ids": [], "corresponding_institution_ids": [], "apc_list": null, "apc_paid": null, "fwci": 13.0621, "has_fulltext": true, "cited_by_count": 366, "citation_normalized_percentile": {"value": 0.99218718, "is_in_top_1_percent": true, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 90, "max": 100}, "biblio": {"volume": null, "issue": null, "first_page": "355", "last_page": "362"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9998999834060669, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9998999834060669, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10664", "display_name": "Sentiment Analysis and Opinion Mining", "score": 0.9998000264167786, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T13083", "display_name": "Advanced Text Analysis Techniques", "score": 0.9993000030517578, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/crfs", "display_name": "CRFS", "score": 0.9667043685913086}, {"id": "https://openalex.org/keywords/conditional-random-field", "display_name": "Conditional random field", "score": 0.9394441843032837}, {"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.7646350860595703}, {"id": "https://openalex.org/keywords/sentiment-analysis", "display_name": "Sentiment analysis", "score": 0.6781970858573914}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.6294721364974976}, {"id": "https://openalex.org/keywords/task", "display_name": "Task (project management)", "score": 0.5986171960830688}, {"id": "https://openalex.org/keywords/matching", "display_name": "Matching (statistics)", "score": 0.5853525400161743}, {"id": "https://openalex.org/keywords/recall", "display_name": "Recall", "score": 0.5793160200119019}, {"id": "https://openalex.org/keywords/natural-language-processing", "display_name": "Natural language processing", "score": 0.5475115776062012}, {"id": "https://openalex.org/keywords/identification", "display_name": "Identification (biology)", "score": 0.5473754405975342}, {"id": "https://openalex.org/keywords/precision-and-recall", "display_name": "Precision and recall", "score": 0.541658878326416}, {"id": "https://openalex.org/keywords/sequence-labeling", "display_name": "Sequence labeling", "score": 0.503011167049408}, {"id": "https://openalex.org/keywords/measure", "display_name": "Measure (data warehouse)", "score": 0.4438106417655945}, {"id": "https://openalex.org/keywords/polarity", "display_name": "Polarity (international relations)", "score": 0.428046852350235}, {"id": "https://openalex.org/keywords/random-forest", "display_name": "Random forest", "score": 0.4273913502693176}, {"id": "https://openalex.org/keywords/information-extraction", "display_name": "Information extraction", "score": 0.4175727367401123}, {"id": "https://openalex.org/keywords/noun", "display_name": "Noun", "score": 0.4125326871871948}, {"id": "https://openalex.org/keywords/data-mining", "display_name": "Data mining", "score": 0.22921273112297058}, {"id": "https://openalex.org/keywords/statistics", "display_name": "Statistics", "score": 0.11832177639007568}, {"id": "https://openalex.org/keywords/mathematics", "display_name": "Mathematics", "score": 0.10403266549110413}, {"id": "https://openalex.org/keywords/linguistics", "display_name": "Linguistics", "score": 0.07506096363067627}], "concepts": [{"id": "https://openalex.org/C2775953691", "wikidata": "https://www.wikidata.org/wiki/Q5013874", "display_name": "CRFS", "level": 3, "score": 0.9667043685913086}, {"id": "https://openalex.org/C152565575", "wikidata": "https://www.wikidata.org/wiki/Q1124538", "display_name": "Conditional random field", "level": 2, "score": 0.9394441843032837}, {"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.7646350860595703}, {"id": "https://openalex.org/C66402592", "wikidata": "https://www.wikidata.org/wiki/Q2271421", "display_name": "Sentiment analysis", "level": 2, "score": 0.6781970858573914}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.6294721364974976}, {"id": "https://openalex.org/C2780451532", "wikidata": "https://www.wikidata.org/wiki/Q759676", "display_name": "Task (project management)", "level": 2, "score": 0.5986171960830688}, {"id": "https://openalex.org/C165064840", "wikidata": "https://www.wikidata.org/wiki/Q1321061", "display_name": "Matching (statistics)", "level": 2, "score": 0.5853525400161743}, {"id": "https://openalex.org/C100660578", "wikidata": "https://www.wikidata.org/wiki/Q18733", "display_name": "Recall", "level": 2, "score": 0.5793160200119019}, {"id": "https://openalex.org/C204321447", "wikidata": "https://www.wikidata.org/wiki/Q30642", "display_name": "Natural language processing", "level": 1, "score": 0.5475115776062012}, {"id": "https://openalex.org/C116834253", "wikidata": "https://www.wikidata.org/wiki/Q2039217", "display_name": "Identification (biology)", "level": 2, "score": 0.5473754405975342}, {"id": "https://openalex.org/C81669768", "wikidata": "https://www.wikidata.org/wiki/Q2359161", "display_name": "Precision and recall", "level": 2, "score": 0.541658878326416}, {"id": "https://openalex.org/C35639132", "wikidata": "https://www.wikidata.org/wiki/Q7452468", "display_name": "Sequence labeling", "level": 3, "score": 0.503011167049408}, {"id": "https://openalex.org/C2780009758", "wikidata": "https://www.wikidata.org/wiki/Q6804172", "display_name": "Measure (data warehouse)", "level": 2, "score": 0.4438106417655945}, {"id": "https://openalex.org/C2777361361", "wikidata": "https://www.wikidata.org/wiki/Q1112585", "display_name": "Polarity (international relations)", "level": 3, "score": 0.428046852350235}, {"id": "https://openalex.org/C169258074", "wikidata": "https://www.wikidata.org/wiki/Q245748", "display_name": "Random forest", "level": 2, "score": 0.4273913502693176}, {"id": "https://openalex.org/C195807954", "wikidata": "https://www.wikidata.org/wiki/Q1662562", "display_name": "Information extraction", "level": 2, "score": 0.4175727367401123}, {"id": "https://openalex.org/C121934690", "wikidata": "https://www.wikidata.org/wiki/Q1084", "display_name": "Noun", "level": 2, "score": 0.4125326871871948}, {"id": "https://openalex.org/C124101348", "wikidata": "https://www.wikidata.org/wiki/Q172491", "display_name": "Data mining", "level": 1, "score": 0.22921273112297058}, {"id": "https://openalex.org/C105795698", "wikidata": "https://www.wikidata.org/wiki/Q12483", "display_name": "Statistics", "level": 1, "score": 0.11832177639007568}, {"id": "https://openalex.org/C33923547", "wikidata": "https://www.wikidata.org/wiki/Q395", "display_name": "Mathematics", "level": 0, "score": 0.10403266549110413}, {"id": "https://openalex.org/C41895202", "wikidata": "https://www.wikidata.org/wiki/Q8162", "display_name": "Linguistics", "level": 1, "score": 0.07506096363067627}, {"id": "https://openalex.org/C59822182", "wikidata": "https://www.wikidata.org/wiki/Q441", "display_name": "Botany", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C162324750", "wikidata": "https://www.wikidata.org/wiki/Q8134", "display_name": "Economics", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C54355233", "wikidata": "https://www.wikidata.org/wiki/Q7162", "display_name": "Genetics", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C187736073", "wikidata": "https://www.wikidata.org/wiki/Q2920921", "display_name": "Management", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C138885662", "wikidata": "https://www.wikidata.org/wiki/Q5891", "display_name": "Philosophy", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C86803240", "wikidata": "https://www.wikidata.org/wiki/Q420", "display_name": "Biology", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C1491633281", "wikidata": "https://www.wikidata.org/wiki/Q7868", "display_name": "Cell", "level": 2, "score": 0.0}], "mesh": [], "locations_count": 5, "locations": [{"id": "doi:10.3115/1220575.1220620", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1220575.1220620", "pdf_url": "https://dl.acm.org/doi/pdf/10.3115/1220575.1220620", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing - HLT '05", "raw_type": "proceedings-article"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.125.6906", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.125.6906", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cs.utah.edu/~sidd/papers/ChoiCRP05.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.143.9004", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.143.9004", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://acl.ldc.upenn.edu/H/H05/H05-1045.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.63.3498", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.63.3498", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www-connex.lip6.fr/~amini/RelatedWorks/EMNLP05-ChoiCardie.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.78.2185", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.78.2185", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cs.utah.edu/~riloff/pdfs/emnlp05.pdf", "raw_type": "text"}], "best_oa_location": {"id": "doi:10.3115/1220575.1220620", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1220575.1220620", "pdf_url": "https://dl.acm.org/doi/pdf/10.3115/1220575.1220620", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing - HLT '05", "raw_type": "proceedings-article"}, "sustainable_development_goals": [{"display_name": "Quality Education", "score": 0.4399999976158142, "id": "https://metadata.un.org/sdg/4"}], "awards": [{"id": "https://openalex.org/G5650125264", "display_name": "Collaborative:  Improving Subjectivity Analysis to Achieve High-Precision Information Extraction", "funder_award_id": "0208985", "funder_id": "https://openalex.org/F4320306076", "funder_display_name": "National Science Foundation"}, {"id": "https://openalex.org/G7813061855", "display_name": "Reducing the Corpus Annotation Bottleneck for Natural Language Learning", "funder_award_id": "0208028", "funder_id": "https://openalex.org/F4320306076", "funder_display_name": "National Science Foundation"}], "funders": [{"id": "https://openalex.org/F4320306076", "display_name": "National Science Foundation", "ror": "https://ror.org/021nxhr62"}, {"id": "https://openalex.org/F4320307101", "display_name": "Xerox Foundation", "ror": "https://ror.org/03jwzwq24"}, {"id": "https://openalex.org/F4320314997", "display_name": "Strong", "ror": "https://ror.org/041vyzr56"}, {"id": "https://openalex.org/F4320323106", "display_name": "Agricultural Research Development Agency", "ror": "https://ror.org/01shbv660"}, {"id": "https://openalex.org/F4320334529", "display_name": "School of Computing, University of Utah", "ror": null}], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2136140395.pdf", "grobid_xml": "https://content.openalex.org/works/W2136140395.grobid-xml"}, "referenced_works_count": 32, "referenced_works": ["https://openalex.org/W4508078", "https://openalex.org/W43269249", "https://openalex.org/W135700821", "https://openalex.org/W206087378", "https://openalex.org/W649466005", "https://openalex.org/W1493379323", "https://openalex.org/W1549016832", "https://openalex.org/W1964654922", "https://openalex.org/W1982229380", "https://openalex.org/W2014902591", "https://openalex.org/W2017238344", "https://openalex.org/W2039217078", "https://openalex.org/W2080558111", "https://openalex.org/W2088622183", "https://openalex.org/W2092654472", "https://openalex.org/W2114524997", "https://openalex.org/W2115023510", "https://openalex.org/W2115792525", "https://openalex.org/W2124634352", "https://openalex.org/W2126854223", "https://openalex.org/W2132755836", "https://openalex.org/W2139193890", "https://openalex.org/W2141099517", "https://openalex.org/W2147880316", "https://openalex.org/W2155328222", "https://openalex.org/W2158188757", "https://openalex.org/W2158847908", "https://openalex.org/W2163918411", "https://openalex.org/W2166706824", "https://openalex.org/W2607879133", "https://openalex.org/W3146306708", "https://openalex.org/W4302585900"], "related_works": ["https://openalex.org/W2962906565", "https://openalex.org/W2798423868", "https://openalex.org/W3015678144", "https://openalex.org/W2076440176", "https://openalex.org/W2055466819", "https://openalex.org/W2140585957", "https://openalex.org/W2054134081", "https://openalex.org/W1675450783", "https://openalex.org/W2061027419", "https://openalex.org/W189110383"], "abstract_inverted_index": {"Recent": [0], "systems": [1], "have": [2], "been": [3], "developed": [4], "for": [5], "sentiment": [6], "classification,": [7], "opinion": [8, 11, 23, 97], "recognition,": [9], "and": [10, 16, 31, 42, 56, 102, 111, 114], "analysis": [12], "(e.g.,": [13], "detecting": [14], "polarity": [15], "strength).": [17], "We": [18, 33], "pursue": [19], "another": [20], "aspect": [21], "of": [22, 28, 59, 83], "analysis:": [24], "identifying": [25], "the": [26, 81], "sources": [27, 98], "opinions,": [29], "emotions,": [30], "sentiments.": [32], "view": [34], "this": [35], "problem": [36], "as": [37, 68], "an": [38, 118], "information": [39], "extraction": [40, 75], "task": [41], "adopt": [43], "a": [44, 57, 69, 106], "hybrid": [45], "approach": [46], "that": [47, 80], "combines": [48], "Conditional": [49], "Random": [50], "Fields": [51], "(Lafferty": [52], "et": [53], "al.,": [54], "2001)": [55], "variation": [58], "AutoSlog": [60, 73], "(Riloff,": [61], "1996a).": [62], "While": [63], "CRFs": [64], "model": [65], "source": [66], "identification": [67], "sequence": [70], "tagging": [71], "task,": [72], "learns": [74], "patterns.": [76], "Our": [77], "results": [78], "show": [79], "combination": [82], "these": [84], "two": [85], "methods": [86], "performs": [87], "better": [88], "than": [89], "either": [90], "one": [91], "alone.": [92], "The": [93], "resulting": [94], "system": [95], "identifies": [96], "with": [99], "79.3%": [100], "precision": [101, 113], "59.5%": [103], "recall": [104, 116], "using": [105, 117], "head": [107], "noun": [108], "matching": [109], "measure,": [110], "81.2%": [112], "60.6%": [115], "overlap": [119], "measure.": [120]}, "counts_by_year": [{"year": 2026, "cited_by_count": 1}, {"year": 2025, "cited_by_count": 1}, {"year": 2024, "cited_by_count": 1}, {"year": 2023, "cited_by_count": 5}, {"year": 2022, "cited_by_count": 7}, {"year": 2021, "cited_by_count": 12}, {"year": 2020, "cited_by_count": 27}, {"year": 2019, "cited_by_count": 9}, {"year": 2018, "cited_by_count": 17}, {"year": 2017, "cited_by_count": 14}, {"year": 2016, "cited_by_count": 22}, {"year": 2015, "cited_by_count": 30}, {"year": 2014, "cited_by_count": 30}, {"year": 2013, "cited_by_count": 20}, {"year": 2012, "cited_by_count": 32}], "updated_date": "2026-07-29T14:22:42.915294", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W1828163288", "doi": "https://doi.org/10.48550/arxiv.1211.3711", "title": "Sequence Transduction with Recurrent Neural Networks", "display_name": "Sequence Transduction with Recurrent Neural Networks", "relevance_score": 488.31155, "publication_year": 2012, "publication_date": "2012-11-14", "ids": {"openalex": "https://openalex.org/W1828163288", "doi": "https://doi.org/10.48550/arxiv.1211.3711", "mag": "1828163288"}, "language": "en", "primary_location": {"id": "pmh:oai:arXiv.org:1211.3711", "is_oa": true, "landing_page_url": "http://arxiv.org/abs/1211.3711", "pdf_url": "https://arxiv.org/pdf/1211.3711", "source": {"id": "https://openalex.org/S4306400194", "display_name": "arXiv (Cornell University)", "issn_l": "2331-8422", "issn": ["2331-8422"], "is_oa": true, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I205783295", "host_organization_name": "Cornell University", "host_organization_lineage": ["https://openalex.org/I205783295"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "", "raw_type": null}, "type": "preprint", "indexed_in": ["arxiv", "datacite"], "open_access": {"is_oa": true, "oa_status": "green", "oa_url": "https://arxiv.org/pdf/1211.3711", "any_repository_has_fulltext": true}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5043473089", "display_name": "Alex Graves", "orcid": null}, "institutions": [{"id": "https://openalex.org/I185261750", "display_name": "University of Toronto", "ror": "https://ror.org/03dbr7087", "country_code": "CA", "type": "education", "lineage": ["https://openalex.org/I185261750"]}], "countries": ["CA"], "is_corresponding": true, "raw_author_name": "Graves, Alex", "raw_affiliation_strings": ["University of Toronto"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Toronto", "institution_ids": ["https://openalex.org/I185261750"]}]}], "institutions": [], "countries_distinct_count": 1, "institutions_distinct_count": 1, "corresponding_author_ids": ["https://openalex.org/A5043473089"], "corresponding_institution_ids": ["https://openalex.org/I185261750"], "apc_list": null, "apc_paid": null, "fwci": null, "has_fulltext": true, "cited_by_count": 1295, "citation_normalized_percentile": null, "cited_by_percentile_year": null, "biblio": {"volume": null, "issue": null, "first_page": null, "last_page": null}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 0.9997000098228455, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 0.9997000098228455, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10201", "display_name": "Speech Recognition and Synthesis", "score": 0.9994000196456909, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9975000023841858, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/transduction", "display_name": "Transduction (biophysics)", "score": 0.8552137017250061}, {"id": "https://openalex.org/keywords/timit", "display_name": "TIMIT", "score": 0.7805290222167969}, {"id": "https://openalex.org/keywords/sequence", "display_name": "Sequence (biology)", "score": 0.6705595850944519}, {"id": "https://openalex.org/keywords/recurrent-neural-network", "display_name": "Recurrent neural network", "score": 0.6703433990478516}, {"id": "https://openalex.org/keywords/sequence-learning", "display_name": "Sequence learning", "score": 0.5693710446357727}, {"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.5569851398468018}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.4935389757156372}, {"id": "https://openalex.org/keywords/speech-recognition", "display_name": "Speech recognition", "score": 0.3658154606819153}, {"id": "https://openalex.org/keywords/artificial-neural-network", "display_name": "Artificial neural network", "score": 0.3380777835845947}, {"id": "https://openalex.org/keywords/hidden-markov-model", "display_name": "Hidden Markov model", "score": 0.21098771691322327}, {"id": "https://openalex.org/keywords/biology", "display_name": "Biology", "score": 0.09661552309989929}, {"id": "https://openalex.org/keywords/genetics", "display_name": "Genetics", "score": 0.061757296323776245}], "concepts": [{"id": "https://openalex.org/C15152581", "wikidata": "https://www.wikidata.org/wiki/Q7833966", "display_name": "Transduction (biophysics)", "level": 2, "score": 0.8552137017250061}, {"id": "https://openalex.org/C2778724510", "wikidata": "https://www.wikidata.org/wiki/Q7670405", "display_name": "TIMIT", "level": 3, "score": 0.7805290222167969}, {"id": "https://openalex.org/C2778112365", "wikidata": "https://www.wikidata.org/wiki/Q3511065", "display_name": "Sequence (biology)", "level": 2, "score": 0.6705595850944519}, {"id": "https://openalex.org/C147168706", "wikidata": "https://www.wikidata.org/wiki/Q1457734", "display_name": "Recurrent neural network", "level": 3, "score": 0.6703433990478516}, {"id": "https://openalex.org/C40506919", "wikidata": "https://www.wikidata.org/wiki/Q7452469", "display_name": "Sequence learning", "level": 2, "score": 0.5693710446357727}, {"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.5569851398468018}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.4935389757156372}, {"id": "https://openalex.org/C28490314", "wikidata": "https://www.wikidata.org/wiki/Q189436", "display_name": "Speech recognition", "level": 1, "score": 0.3658154606819153}, {"id": "https://openalex.org/C50644808", "wikidata": "https://www.wikidata.org/wiki/Q192776", "display_name": "Artificial neural network", "level": 2, "score": 0.3380777835845947}, {"id": "https://openalex.org/C23224414", "wikidata": "https://www.wikidata.org/wiki/Q176769", "display_name": "Hidden Markov model", "level": 2, "score": 0.21098771691322327}, {"id": "https://openalex.org/C86803240", "wikidata": "https://www.wikidata.org/wiki/Q420", "display_name": "Biology", "level": 0, "score": 0.09661552309989929}, {"id": "https://openalex.org/C54355233", "wikidata": "https://www.wikidata.org/wiki/Q7162", "display_name": "Genetics", "level": 1, "score": 0.061757296323776245}, {"id": "https://openalex.org/C55493867", "wikidata": "https://www.wikidata.org/wiki/Q7094", "display_name": "Biochemistry", "level": 1, "score": 0.0}], "mesh": [], "locations_count": 4, "locations": [{"id": "pmh:oai:arXiv.org:1211.3711", "is_oa": true, "landing_page_url": "http://arxiv.org/abs/1211.3711", "pdf_url": "https://arxiv.org/pdf/1211.3711", "source": {"id": "https://openalex.org/S4306400194", "display_name": "arXiv (Cornell University)", "issn_l": "2331-8422", "issn": ["2331-8422"], "is_oa": true, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I205783295", "host_organization_name": "Cornell University", "host_organization_lineage": ["https://openalex.org/I205783295"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "", "raw_type": null}, {"id": "mag:1828163288", "is_oa": true, "landing_page_url": "https://arxiv.org/pdf/1211.3711.pdf", "pdf_url": null, "source": {"id": "https://openalex.org/S4306400194", "display_name": "arXiv (Cornell University)", "issn_l": "2331-8422", "issn": ["2331-8422"], "is_oa": true, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I205783295", "host_organization_name": "Cornell University", "host_organization_lineage": ["https://openalex.org/I205783295"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "arXiv (Cornell University)", "raw_type": null}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.756.8616", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.756.8616", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://arxiv.org/pdf/1211.3711.pdf", "raw_type": "text"}, {"id": "doi:10.48550/arxiv.1211.3711", "is_oa": true, "landing_page_url": "https://doi.org/10.48550/arxiv.1211.3711", "pdf_url": null, "source": {"id": "https://openalex.org/S4306400194", "display_name": "arXiv (Cornell University)", "issn_l": "2331-8422", "issn": ["2331-8422"], "is_oa": true, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I205783295", "host_organization_name": "Cornell University", "host_organization_lineage": ["https://openalex.org/I205783295"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": null, "is_accepted": false, "is_published": null, "raw_source_name": null, "raw_type": "Preprint"}], "best_oa_location": {"id": "pmh:oai:arXiv.org:1211.3711", "is_oa": true, "landing_page_url": "http://arxiv.org/abs/1211.3711", "pdf_url": "https://arxiv.org/pdf/1211.3711", "source": {"id": "https://openalex.org/S4306400194", "display_name": "arXiv (Cornell University)", "issn_l": "2331-8422", "issn": ["2331-8422"], "is_oa": true, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I205783295", "host_organization_name": "Cornell University", "host_organization_lineage": ["https://openalex.org/I205783295"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "", "raw_type": null}, "sustainable_development_goals": [{"display_name": "Quality Education", "score": 0.46000000834465027, "id": "https://metadata.un.org/sdg/4"}], "awards": [], "funders": [], "has_content": {"grobid_xml": false, "pdf": false}, "content_urls": null, "referenced_works_count": 20, "referenced_works": ["https://openalex.org/W179875071", "https://openalex.org/W196214544", "https://openalex.org/W1525783482", "https://openalex.org/W1674799117", "https://openalex.org/W1902568950", "https://openalex.org/W1964175594", "https://openalex.org/W2053831280", "https://openalex.org/W2064675550", "https://openalex.org/W2077804127", "https://openalex.org/W2079735306", "https://openalex.org/W2103359087", "https://openalex.org/W2112796928", "https://openalex.org/W2127141656", "https://openalex.org/W2131283257", "https://openalex.org/W2131774270", "https://openalex.org/W2147880316", "https://openalex.org/W2167898728", "https://openalex.org/W2170942820", "https://openalex.org/W3023071679", "https://openalex.org/W3127686677"], "related_works": ["https://openalex.org/W854541894", "https://openalex.org/W2964308564", "https://openalex.org/W2964121744", "https://openalex.org/W2963414781", "https://openalex.org/W2963403868", "https://openalex.org/W2962826786", "https://openalex.org/W2962824709", "https://openalex.org/W2962760690", "https://openalex.org/W2936774411", "https://openalex.org/W2526425061", "https://openalex.org/W2327501763", "https://openalex.org/W2160815625", "https://openalex.org/W2157331557", "https://openalex.org/W2143612262", "https://openalex.org/W2130942839", "https://openalex.org/W2127141656", "https://openalex.org/W2102113734", "https://openalex.org/W2064675550", "https://openalex.org/W1524333225", "https://openalex.org/W1494198834"], "abstract_inverted_index": {"Many": [0], "machine": [1, 18], "learning": [2, 40, 72, 79], "tasks": [3], "can": [4], "be": [5], "expressed": [6], "as": [7, 59], "the": [8, 33, 44, 90, 105, 108, 120, 123, 166], "transformation---or": [9], "\\emph{transduction}---of": [10], "input": [11, 45, 91, 150], "sequences": [12, 48, 94], "into": [13, 152], "output": [14, 47, 93, 124, 156], "sequences:": [15], "speech": [16, 168], "recognition,": [17], "translation,": [19], "protein": [20], "secondary": [21], "structure": [22], "prediction": [23], "and": [24, 46, 62, 92], "text-to-speech": [25], "to": [26, 41, 55, 95, 147], "name": [27], "but": [28], "a": [29, 50, 69, 86, 100], "few.": [30], "One": [31], "of": [32, 78, 112, 122], "key": [34], "challenges": [35], "in": [36, 49, 144], "sequence": [37, 71, 114, 125, 135, 151], "transduction": [38, 115, 136], "is": [39, 53, 99, 107, 126, 143], "represent": [42], "both": [43], "way": [51], "that": [52, 74, 142], "invariant": [54], "sequential": [56], "distortions": [57], "such": [58, 80], "shrinking,": [60], "stretching": [61], "translating.": [63], "Recurrent": [64], "neural": [65], "networks": [66], "(RNNs)": [67], "are": [68, 163], "powerful": [70], "architecture": [73], "has": [75], "proven": [76], "capable": [77], "representations.": [81], "However": [82], "RNNs": [83], "traditionally": [84], "require": [85], "pre-defined": [87], "alignment": [88, 106], "between": [89], "perform": [96], "transduction.": [97], "This": [98, 129], "severe": [101], "limitation": [102], "since": [103], "\\emph{finding}": [104], "most": [109], "difficult": [110], "aspect": [111], "many": [113], "problems.": [116], "Indeed,": [117], "even": [118], "determining": [119], "length": [121], "often": [127], "challenging.": [128], "paper": [130], "introduces": [131], "an": [132], "end-to-end,": [133], "probabilistic": [134], "system,": [137], "based": [138], "entirely": [139], "on": [140, 165], "RNNs,": [141], "principle": [145], "able": [146], "transform": [148], "any": [149, 153], "finite,": [154], "discrete": [155], "sequence.": [157], "Experimental": [158], "results": [159], "for": [160], "phoneme": [161], "recognition": [162], "provided": [164], "TIMIT": [167], "corpus.": [169]}, "counts_by_year": [{"year": 2025, "cited_by_count": 20}, {"year": 2024, "cited_by_count": 35}, {"year": 2023, "cited_by_count": 200}, {"year": 2022, "cited_by_count": 161}, {"year": 2021, "cited_by_count": 323}, {"year": 2020, "cited_by_count": 205}, {"year": 2019, "cited_by_count": 142}, {"year": 2018, "cited_by_count": 83}, {"year": 2017, "cited_by_count": 46}, {"year": 2016, "cited_by_count": 30}, {"year": 2015, "cited_by_count": 19}, {"year": 2014, "cited_by_count": 19}, {"year": 2013, "cited_by_count": 10}, {"year": 2012, "cited_by_count": 2}], "updated_date": "2026-08-05T07:39:15.569665", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W2139193890", "doi": "https://doi.org/10.48550/arxiv.1212.2504", "title": "Efficiently Inducing Features of Conditional Random Fields", "display_name": "Efficiently Inducing Features of Conditional Random Fields", "relevance_score": 487.80432, "publication_year": 2012, "publication_date": "2012-10-19", "ids": {"openalex": "https://openalex.org/W2139193890", "doi": "https://doi.org/10.48550/arxiv.1212.2504", "mag": "2139193890"}, "language": "en", "primary_location": {"id": "pmh:oai:arXiv.org:1212.2504", "is_oa": true, "landing_page_url": "http://arxiv.org/abs/1212.2504", "pdf_url": "https://arxiv.org/pdf/1212.2504", "source": {"id": "https://openalex.org/S4306400194", "display_name": "arXiv (Cornell University)", "issn_l": "2331-8422", "issn": ["2331-8422"], "is_oa": true, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I205783295", "host_organization_name": "Cornell University", "host_organization_lineage": ["https://openalex.org/I205783295"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "", "raw_type": "text"}, "type": "preprint", "indexed_in": ["arxiv", "datacite"], "open_access": {"is_oa": true, "oa_status": "green", "oa_url": "https://arxiv.org/pdf/1212.2504", "any_repository_has_fulltext": true}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5107835063", "display_name": "Andrew McCallum", "orcid": null}, "institutions": [{"id": "https://openalex.org/I24603500", "display_name": "University of Massachusetts Amherst", "ror": "https://ror.org/0072zz521", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I24603500"]}], "countries": ["US"], "is_corresponding": true, "raw_author_name": "McCallum, Andrew", "raw_affiliation_strings": ["Computer Science Department, University of Massachusetts Amherst, Amherst MA#TAB#"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Computer Science Department, University of Massachusetts Amherst, Amherst MA#TAB#", "institution_ids": ["https://openalex.org/I24603500"]}]}], "institutions": [], "countries_distinct_count": 1, "institutions_distinct_count": 1, "corresponding_author_ids": ["https://openalex.org/A5107835063"], "corresponding_institution_ids": ["https://openalex.org/I24603500"], "apc_list": null, "apc_paid": null, "fwci": null, "has_fulltext": true, "cited_by_count": 366, "citation_normalized_percentile": null, "cited_by_percentile_year": null, "biblio": {"volume": null, "issue": null, "first_page": "403", "last_page": "410"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9998999834060669, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9998999834060669, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 0.9997000098228455, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T11719", "display_name": "Data Quality and Management", "score": 0.9987999796867371, "subfield": {"id": "https://openalex.org/subfields/1803", "display_name": "Management Science and Operations Research"}, "field": {"id": "https://openalex.org/fields/18", "display_name": "Decision Sciences"}, "domain": {"id": "https://openalex.org/domains/2", "display_name": "Social Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/crfs", "display_name": "CRFS", "score": 0.9457402229309082}, {"id": "https://openalex.org/keywords/conditional-random-field", "display_name": "Conditional random field", "score": 0.8603039979934692}, {"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.6642913222312927}, {"id": "https://openalex.org/keywords/feature", "display_name": "Feature (linguistics)", "score": 0.6098001003265381}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.6073564291000366}, {"id": "https://openalex.org/keywords/sequence-labeling", "display_name": "Sequence labeling", "score": 0.5520539283752441}, {"id": "https://openalex.org/keywords/graphical-model", "display_name": "Graphical model", "score": 0.5335728526115417}, {"id": "https://openalex.org/keywords/markov-chain", "display_name": "Markov chain", "score": 0.5094752907752991}, {"id": "https://openalex.org/keywords/maximum-entropy-markov-model", "display_name": "Maximum-entropy Markov model", "score": 0.4840599596500397}, {"id": "https://openalex.org/keywords/flexibility", "display_name": "Flexibility (engineering)", "score": 0.4735400080680847}, {"id": "https://openalex.org/keywords/pattern-recognition", "display_name": "Pattern recognition (psychology)", "score": 0.4724065661430359}, {"id": "https://openalex.org/keywords/hidden-markov-model", "display_name": "Hidden Markov model", "score": 0.41561856865882874}, {"id": "https://openalex.org/keywords/chain-rule", "display_name": "Chain rule (probability)", "score": 0.41181179881095886}, {"id": "https://openalex.org/keywords/machine-learning", "display_name": "Machine learning", "score": 0.4075917601585388}, {"id": "https://openalex.org/keywords/variable-order-markov-model", "display_name": "Variable-order Markov model", "score": 0.37229302525520325}, {"id": "https://openalex.org/keywords/markov-model", "display_name": "Markov model", "score": 0.31167909502983093}, {"id": "https://openalex.org/keywords/task", "display_name": "Task (project management)", "score": 0.2826608419418335}, {"id": "https://openalex.org/keywords/mathematics", "display_name": "Mathematics", "score": 0.24050799012184143}, {"id": "https://openalex.org/keywords/regular-conditional-probability", "display_name": "Regular conditional probability", "score": 0.1344144642353058}, {"id": "https://openalex.org/keywords/posterior-probability", "display_name": "Posterior probability", "score": 0.1096276342868805}], "concepts": [{"id": "https://openalex.org/C2775953691", "wikidata": "https://www.wikidata.org/wiki/Q5013874", "display_name": "CRFS", "level": 3, "score": 0.9457402229309082}, {"id": "https://openalex.org/C152565575", "wikidata": "https://www.wikidata.org/wiki/Q1124538", "display_name": "Conditional random field", "level": 2, "score": 0.8603039979934692}, {"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.6642913222312927}, {"id": "https://openalex.org/C2776401178", "wikidata": "https://www.wikidata.org/wiki/Q12050496", "display_name": "Feature (linguistics)", "level": 2, "score": 0.6098001003265381}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.6073564291000366}, {"id": "https://openalex.org/C35639132", "wikidata": "https://www.wikidata.org/wiki/Q7452468", "display_name": "Sequence labeling", "level": 3, "score": 0.5520539283752441}, {"id": "https://openalex.org/C155846161", "wikidata": "https://www.wikidata.org/wiki/Q1143367", "display_name": "Graphical model", "level": 2, "score": 0.5335728526115417}, {"id": "https://openalex.org/C98763669", "wikidata": "https://www.wikidata.org/wiki/Q176645", "display_name": "Markov chain", "level": 2, "score": 0.5094752907752991}, {"id": "https://openalex.org/C196956702", "wikidata": "https://www.wikidata.org/wiki/Q6795829", "display_name": "Maximum-entropy Markov model", "level": 5, "score": 0.4840599596500397}, {"id": "https://openalex.org/C2780598303", "wikidata": "https://www.wikidata.org/wiki/Q65921492", "display_name": "Flexibility (engineering)", "level": 2, "score": 0.4735400080680847}, {"id": "https://openalex.org/C153180895", "wikidata": "https://www.wikidata.org/wiki/Q7148389", "display_name": "Pattern recognition (psychology)", "level": 2, "score": 0.4724065661430359}, {"id": "https://openalex.org/C23224414", "wikidata": "https://www.wikidata.org/wiki/Q176769", "display_name": "Hidden Markov model", "level": 2, "score": 0.41561856865882874}, {"id": "https://openalex.org/C33825631", "wikidata": "https://www.wikidata.org/wiki/Q17004731", "display_name": "Chain rule (probability)", "level": 5, "score": 0.41181179881095886}, {"id": "https://openalex.org/C119857082", "wikidata": "https://www.wikidata.org/wiki/Q2539", "display_name": "Machine learning", "level": 1, "score": 0.4075917601585388}, {"id": "https://openalex.org/C54907487", "wikidata": "https://www.wikidata.org/wiki/Q7915688", "display_name": "Variable-order Markov model", "level": 4, "score": 0.37229302525520325}, {"id": "https://openalex.org/C163836022", "wikidata": "https://www.wikidata.org/wiki/Q6771326", "display_name": "Markov model", "level": 3, "score": 0.31167909502983093}, {"id": "https://openalex.org/C2780451532", "wikidata": "https://www.wikidata.org/wiki/Q759676", "display_name": "Task (project management)", "level": 2, "score": 0.2826608419418335}, {"id": "https://openalex.org/C33923547", "wikidata": "https://www.wikidata.org/wiki/Q395", "display_name": "Mathematics", "level": 0, "score": 0.24050799012184143}, {"id": "https://openalex.org/C103982235", "wikidata": "https://www.wikidata.org/wiki/Q7309594", "display_name": "Regular conditional probability", "level": 4, "score": 0.1344144642353058}, {"id": "https://openalex.org/C57830394", "wikidata": "https://www.wikidata.org/wiki/Q278079", "display_name": "Posterior probability", "level": 3, "score": 0.1096276342868805}, {"id": "https://openalex.org/C107673813", "wikidata": "https://www.wikidata.org/wiki/Q812534", "display_name": "Bayesian probability", "level": 2, "score": 0.0}, {"id": "https://openalex.org/C41895202", "wikidata": "https://www.wikidata.org/wiki/Q8162", "display_name": "Linguistics", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C105795698", "wikidata": "https://www.wikidata.org/wiki/Q12483", "display_name": "Statistics", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C138885662", "wikidata": "https://www.wikidata.org/wiki/Q5891", "display_name": "Philosophy", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C187736073", "wikidata": "https://www.wikidata.org/wiki/Q2920921", "display_name": "Management", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C162324750", "wikidata": "https://www.wikidata.org/wiki/Q8134", "display_name": "Economics", "level": 0, "score": 0.0}], "mesh": [], "locations_count": 6, "locations": [{"id": "pmh:oai:arXiv.org:1212.2504", "is_oa": true, "landing_page_url": "http://arxiv.org/abs/1212.2504", "pdf_url": "https://arxiv.org/pdf/1212.2504", "source": {"id": "https://openalex.org/S4306400194", "display_name": "arXiv (Cornell University)", "issn_l": "2331-8422", "issn": ["2331-8422"], "is_oa": true, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I205783295", "host_organization_name": "Cornell University", "host_organization_lineage": ["https://openalex.org/I205783295"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "", "raw_type": "text"}, {"id": "pmh:oai:works.bepress.com:andrew_mccallum-1021", "is_oa": true, "landing_page_url": "https://works.bepress.com/andrew_mccallum/18", "pdf_url": "https://works.bepress.com/andrew_mccallum/18", "source": {"id": "https://openalex.org/S4306402240", "display_name": "ScholarWorks@UMassAmherst (University of Massachusetts Amherst)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I24603500", "host_organization_name": "University of Massachusetts Amherst", "host_organization_lineage": ["https://openalex.org/I24603500"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Andrew McCallum", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.14.1630", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.1630", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cs.umass.edu/~mccallum/papers/ifcrf-uai2003.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.14.7625", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.7625", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cs.umass.edu/~mccallum/papers/ifcrf-uai2003s.pdf", "raw_type": "text"}, {"id": "doi:10.48550/arxiv.1212.2504", "is_oa": true, "landing_page_url": "https://doi.org/10.48550/arxiv.1212.2504", "pdf_url": null, "source": {"id": "https://openalex.org/S4306400194", "display_name": "arXiv (Cornell University)", "issn_l": "2331-8422", "issn": ["2331-8422"], "is_oa": true, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I205783295", "host_organization_name": "Cornell University", "host_organization_lineage": ["https://openalex.org/I205783295"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": null, "is_accepted": false, "is_published": null, "raw_source_name": null, "raw_type": "Preprint"}, {"id": "mag:2139193890", "is_oa": false, "landing_page_url": "http://ciir.cs.umass.edu/pubfiles/ir-304.pdf", "pdf_url": null, "source": {"id": "https://openalex.org/S4306421103", "display_name": "Uncertainty in Artificial Intelligence", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": null, "host_organization_name": null, "host_organization_lineage": [], "host_organization_lineage_names": [], "type": "conference"}, "license": null, "license_id": null, "version": null, "is_accepted": false, "is_published": null, "raw_source_name": "Uncertainty in Artificial Intelligence", "raw_type": null}], "best_oa_location": {"id": "pmh:oai:arXiv.org:1212.2504", "is_oa": true, "landing_page_url": "http://arxiv.org/abs/1212.2504", "pdf_url": "https://arxiv.org/pdf/1212.2504", "source": {"id": "https://openalex.org/S4306400194", "display_name": "arXiv (Cornell University)", "issn_l": "2331-8422", "issn": ["2331-8422"], "is_oa": true, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I205783295", "host_organization_name": "Cornell University", "host_organization_lineage": ["https://openalex.org/I205783295"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "", "raw_type": "text"}, "sustainable_development_goals": [{"display_name": "Peace, Justice and strong institutions", "score": 0.6700000166893005, "id": "https://metadata.un.org/sdg/16"}], "awards": [], "funders": [{"id": "https://openalex.org/F4320332180", "display_name": "Defense Advanced Research Projects Agency", "ror": "https://ror.org/02caytj08"}], "has_content": {"grobid_xml": false, "pdf": false}, "content_urls": null, "referenced_works_count": 23, "referenced_works": ["https://openalex.org/W202303397", "https://openalex.org/W1510793943", "https://openalex.org/W1557074680", "https://openalex.org/W1575332430", "https://openalex.org/W1592796124", "https://openalex.org/W1773803948", "https://openalex.org/W1934019294", "https://openalex.org/W1988790447", "https://openalex.org/W1988995507", "https://openalex.org/W1989568037", "https://openalex.org/W2008652694", "https://openalex.org/W2058839679", "https://openalex.org/W2070013518", "https://openalex.org/W2099942883", "https://openalex.org/W2102667697", "https://openalex.org/W2125838338", "https://openalex.org/W2147880316", "https://openalex.org/W2156515921", "https://openalex.org/W2160842254", "https://openalex.org/W2161290181", "https://openalex.org/W2162186970", "https://openalex.org/W2962735828", "https://openalex.org/W2994982620"], "related_works": ["https://openalex.org/W2160842254", "https://openalex.org/W2156515921", "https://openalex.org/W2147880316", "https://openalex.org/W2141099517", "https://openalex.org/W2125838338", "https://openalex.org/W1934019294", "https://openalex.org/W2159080219", "https://openalex.org/W2008652694", "https://openalex.org/W1766290689", "https://openalex.org/W2102667697", "https://openalex.org/W2034797903", "https://openalex.org/W1977970897", "https://openalex.org/W2962735828", "https://openalex.org/W28766783", "https://openalex.org/W2105644991", "https://openalex.org/W2051434435", "https://openalex.org/W2158188757", "https://openalex.org/W2096175520", "https://openalex.org/W1534730506", "https://openalex.org/W1574901103"], "abstract_inverted_index": {"Conditional": [0], "Random": [1], "Fields": [2], "(CRFs)": [3], "are": [4], "undirected": [5], "graphical": [6], "models,": [7, 146], "a": [8, 31, 61, 112, 162, 194], "special": [9], "case": [10], "of": [11, 22, 34, 39, 44, 71, 87, 132, 142], "which": [12, 155], "correspond": [13], "to": [14, 29, 95, 151, 161, 168, 174], "conditionally-trained": [15], "finite": [16], "state": [17], "machines.": [18], "A": [19], "key": [20], "advantage": [21], "these": [23], "models": [24], "is": [25, 83], "their": [26], "great": [27], "flexibility": [28], "include": [30], "wide": [32], "array": [33], "overlapping,": [35], "multi-granularity,": [36], "non-independent": [37], "features": [38, 54, 157], "the": [40, 69, 81, 140], "input.": [41], "In": [42, 115], "face": [43], "this": [45], "freedom,": [46], "an": [47, 130], "important": [48], "question": [49], "that": [50, 77, 86], "remains": [51], "is,": [52], "what": [53], "should": [55], "be": [56, 159], "used?": [57], "This": [58], "paper": [59], "presents": [60], "feature": [62, 75, 121, 136], "induction": [63, 122, 165], "method": [64, 166], "for": [65, 107, 111], "CRFs.": [66], "Founded": [67], "on": [68, 85, 193], "principle": [70], "constructing": [72], "only": [73], "those": [74], "conjunctions": [76], "significantly": [78], "increase": [79], "log-likelihood,": [80], "approach": [82], "based": [84], "Della": [88], "Pietra": [89], "et": [90], "al": [91], "[1997],": [92], "but": [93], "altered": [94], "work": [96], "with": [97, 104, 117], "conditional": [98], "rather": [99], "than": [100, 129], "joint": [101], "probabilities,": [102], "and": [103, 127, 147], "additional": [105], "modifications": [106], "providing": [108], "tractability": [109], "specifically": [110], "sequence": [113], "model.": [114], "comparison": [116], "traditional": [118], "approaches,": [119], "automated": [120], "offers": [123, 148], "both": [124], "improved": [125], "accuracy": [126], "more": [128, 149, 175], "order": [131], "magnitude": [133], "reduction": [134], "in": [135], "count;": [137], "it": [138], "enables": [139], "use": [141], "richer,": [143], "higher-order": [144], "Markov": [145, 183], "freedom": [150], "liberally": [152], "guess": [153], "about": [154], "atomic": [156], "may": [158], "relevant": [160], "task.": [163, 198], "The": [164], "applies": [167], "linear-chain": [169], "CRFs,": [170], "as": [171, 173, 181], "well": [172], "arbitrary": [176], "CRF": [177], "structures,": [178], "also": [179], "known": [180], "Relational": [182], "Networks": [184], "[Taskar": [185], "&amp;": [186], "Koller,": [187], "2002].": [188], "We": [189], "present": [190], "experimental": [191], "results": [192], "named": [195], "entity": [196], "extraction": [197]}, "counts_by_year": [{"year": 2023, "cited_by_count": 2}, {"year": 2022, "cited_by_count": 2}, {"year": 2021, "cited_by_count": 7}, {"year": 2020, "cited_by_count": 5}, {"year": 2019, "cited_by_count": 11}, {"year": 2018, "cited_by_count": 5}, {"year": 2017, "cited_by_count": 8}, {"year": 2016, "cited_by_count": 15}, {"year": 2015, "cited_by_count": 14}, {"year": 2014, "cited_by_count": 16}, {"year": 2013, "cited_by_count": 22}, {"year": 2012, "cited_by_count": 29}], "updated_date": "2026-07-28T07:46:37.118299", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W2962843214", "doi": "https://doi.org/10.18653/v1/d16-1059", "title": "Recursive Neural Conditional Random Fields for Aspect-based Sentiment Analysis", "display_name": "Recursive Neural Conditional Random Fields for Aspect-based Sentiment Analysis", "relevance_score": 486.57462, "publication_year": 2016, "publication_date": "2016-01-01", "ids": {"openalex": "https://openalex.org/W2962843214", "doi": "https://doi.org/10.18653/v1/d16-1059", "mag": "2962843214"}, "language": "en", "primary_location": {"id": "doi:10.18653/v1/d16-1059", "is_oa": true, "landing_page_url": "https://doi.org/10.18653/v1/d16-1059", "pdf_url": "https://www.aclweb.org/anthology/D16-1059.pdf", "source": null, "license": "cc-by", "license_id": "https://openalex.org/licenses/cc-by", "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing", "raw_type": "proceedings-article"}, "type": "conference-paper", "indexed_in": ["crossref"], "open_access": {"is_oa": true, "oa_status": "gold", "oa_url": "https://www.aclweb.org/anthology/D16-1059.pdf", "any_repository_has_fulltext": null}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5078565848", "display_name": "Wenya Wang", "orcid": "https://orcid.org/0000-0001-5612-7818"}, "institutions": [{"id": "https://openalex.org/I172675005", "display_name": "Nanyang Technological University", "ror": "https://ror.org/02e7b5302", "country_code": "SG", "type": "education", "lineage": ["https://openalex.org/I172675005"]}], "countries": ["SG"], "is_corresponding": false, "raw_author_name": "Wenya Wang", "raw_affiliation_strings": ["Nanyang Technological University, Singapore", "SAP Innovation Center Singapore"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Nanyang Technological University, Singapore", "institution_ids": ["https://openalex.org/I172675005"]}, {"raw_affiliation_string": "SAP Innovation Center Singapore", "institution_ids": []}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5082984558", "display_name": "Sinno Jialin Pan", "orcid": "https://orcid.org/0000-0001-6565-3836"}, "institutions": [{"id": "https://openalex.org/I172675005", "display_name": "Nanyang Technological University", "ror": "https://ror.org/02e7b5302", "country_code": "SG", "type": "education", "lineage": ["https://openalex.org/I172675005"]}], "countries": ["SG"], "is_corresponding": false, "raw_author_name": "Sinno Jialin Pan", "raw_affiliation_strings": ["Nanyang Technological University, Singapore"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Nanyang Technological University, Singapore", "institution_ids": ["https://openalex.org/I172675005"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5002373633", "display_name": "Daniel Dahlmeier", "orcid": null}, "institutions": [], "countries": [], "is_corresponding": false, "raw_author_name": "Daniel Dahlmeier", "raw_affiliation_strings": ["SAP Innovation Center Singapore"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "SAP Innovation Center Singapore", "institution_ids": []}]}, {"author_position": "last", "author": {"id": "https://openalex.org/A5010903591", "display_name": "Xiaokui Xiao", "orcid": "https://orcid.org/0000-0003-0914-4580"}, "institutions": [{"id": "https://openalex.org/I172675005", "display_name": "Nanyang Technological University", "ror": "https://ror.org/02e7b5302", "country_code": "SG", "type": "education", "lineage": ["https://openalex.org/I172675005"]}], "countries": ["SG"], "is_corresponding": false, "raw_author_name": "Xiaokui Xiao", "raw_affiliation_strings": ["Nanyang Technological University, Singapore"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Nanyang Technological University, Singapore", "institution_ids": ["https://openalex.org/I172675005"]}]}], "institutions": [], "countries_distinct_count": 1, "institutions_distinct_count": 1, "corresponding_author_ids": [], "corresponding_institution_ids": [], "apc_list": null, "apc_paid": null, "fwci": 18.054, "has_fulltext": true, "cited_by_count": 427, "citation_normalized_percentile": {"value": 0.9946548, "is_in_top_1_percent": true, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 99, "max": 100}, "biblio": {"volume": null, "issue": null, "first_page": "616", "last_page": "626"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10664", "display_name": "Sentiment Analysis and Opinion Mining", "score": 0.9998000264167786, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10664", "display_name": "Sentiment Analysis and Opinion Mining", "score": 0.9998000264167786, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9972000122070312, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T11550", "display_name": "Text and Document Classification Technologies", "score": 0.9970999956130981, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.6711338758468628}, {"id": "https://openalex.org/keywords/sentiment-analysis", "display_name": "Sentiment analysis", "score": 0.6424515247344971}, {"id": "https://openalex.org/keywords/conditional-random-field", "display_name": "Conditional random field", "score": 0.6357400417327881}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.5058888792991638}, {"id": "https://openalex.org/keywords/natural-language-processing", "display_name": "Natural language processing", "score": 0.3810942769050598}], "concepts": [{"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.6711338758468628}, {"id": "https://openalex.org/C66402592", "wikidata": "https://www.wikidata.org/wiki/Q2271421", "display_name": "Sentiment analysis", "level": 2, "score": 0.6424515247344971}, {"id": "https://openalex.org/C152565575", "wikidata": "https://www.wikidata.org/wiki/Q1124538", "display_name": "Conditional random field", "level": 2, "score": 0.6357400417327881}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.5058888792991638}, {"id": "https://openalex.org/C204321447", "wikidata": "https://www.wikidata.org/wiki/Q30642", "display_name": "Natural language processing", "level": 1, "score": 0.3810942769050598}], "mesh": [], "locations_count": 1, "locations": [{"id": "doi:10.18653/v1/d16-1059", "is_oa": true, "landing_page_url": "https://doi.org/10.18653/v1/d16-1059", "pdf_url": "https://www.aclweb.org/anthology/D16-1059.pdf", "source": null, "license": "cc-by", "license_id": "https://openalex.org/licenses/cc-by", "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing", "raw_type": "proceedings-article"}], "best_oa_location": {"id": "doi:10.18653/v1/d16-1059", "is_oa": true, "landing_page_url": "https://doi.org/10.18653/v1/d16-1059", "pdf_url": "https://www.aclweb.org/anthology/D16-1059.pdf", "source": null, "license": "cc-by", "license_id": "https://openalex.org/licenses/cc-by", "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing", "raw_type": "proceedings-article"}, "sustainable_development_goals": [{"display_name": "Reduced inequalities", "score": 0.75, "id": "https://metadata.un.org/sdg/10"}], "awards": [{"id": "https://openalex.org/G8771026661", "display_name": null, "funder_award_id": "M4081532.020", "funder_id": "https://openalex.org/F4320320766", "funder_display_name": "Nanyang Technological University"}], "funders": [{"id": "https://openalex.org/F4320320671", "display_name": "National Research Foundation", "ror": "https://ror.org/05s0g1g46"}, {"id": "https://openalex.org/F4320320709", "display_name": "National Research Foundation Singapore", "ror": "https://ror.org/03cpyc314"}, {"id": "https://openalex.org/F4320320766", "display_name": "Nanyang Technological University", "ror": "https://ror.org/02e7b5302"}], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2962843214.pdf", "grobid_xml": "https://content.openalex.org/works/W2962843214.grobid-xml"}, "referenced_works_count": 51, "referenced_works": ["https://openalex.org/W22861983", "https://openalex.org/W71795751", "https://openalex.org/W182185074", "https://openalex.org/W1026216613", "https://openalex.org/W1423339008", "https://openalex.org/W1515087027", "https://openalex.org/W1517771839", "https://openalex.org/W1581485226", "https://openalex.org/W1614298861", "https://openalex.org/W1832693441", "https://openalex.org/W1859957297", "https://openalex.org/W1889268436", "https://openalex.org/W1991819034", "https://openalex.org/W1996430422", "https://openalex.org/W2001259128", "https://openalex.org/W2019207508", "https://openalex.org/W2027731328", "https://openalex.org/W2049493498", "https://openalex.org/W2064675550", "https://openalex.org/W2081375810", "https://openalex.org/W2096141509", "https://openalex.org/W2097606805", "https://openalex.org/W2097726431", "https://openalex.org/W2100362224", "https://openalex.org/W2104518905", "https://openalex.org/W2112744748", "https://openalex.org/W2117499988", "https://openalex.org/W2120615054", "https://openalex.org/W2125247664", "https://openalex.org/W2130237711", "https://openalex.org/W2131305515", "https://openalex.org/W2131744502", "https://openalex.org/W2137207778", "https://openalex.org/W2144012961", "https://openalex.org/W2147880316", "https://openalex.org/W2149557440", "https://openalex.org/W2154970197", "https://openalex.org/W2159457224", "https://openalex.org/W2160660844", "https://openalex.org/W2161222299", "https://openalex.org/W2161672051", "https://openalex.org/W2251124635", "https://openalex.org/W2251648804", "https://openalex.org/W2251939518", "https://openalex.org/W2252024663", "https://openalex.org/W2269911130", "https://openalex.org/W2328290429", "https://openalex.org/W2963556938", "https://openalex.org/W3049711450", "https://openalex.org/W4248506559", "https://openalex.org/W4299026567"], "related_works": ["https://openalex.org/W2899084033", "https://openalex.org/W2748952813", "https://openalex.org/W2356597680", "https://openalex.org/W2114846443", "https://openalex.org/W2093471820", "https://openalex.org/W3102147106", "https://openalex.org/W2347460059", "https://openalex.org/W50079190", "https://openalex.org/W2886890203", "https://openalex.org/W3192589309"], "abstract_inverted_index": {"In": [0, 40], "aspect-based": [1], "sentiment": [2], "analysis,": [3], "extracting": [4], "aspect": [5, 31, 64, 81], "terms": [6, 34, 67], "along": [7], "with": [8], "the": [9, 19, 95, 108, 117, 130, 134], "opinions": [10], "being": [11], "expressed": [12], "from": [13, 110], "user-generated": [14], "content": [15], "is": [16, 35, 88], "one": [17], "of": [18, 119, 133], "most": [20], "important": [21], "subtasks.": [22], "Previous": [23], "studies": [24], "have": [25], "shown": [26], "that": [27, 49], "exploiting": [28], "connections": [29], "between": [30, 80], "and": [32, 54, 65, 76, 82], "opinion": [33, 66, 83], "promising": [36], "for": [37, 62], "this": [38, 41], "task.": [39], "paper,": [42], "we": [43], "propose": [44], "a": [45, 59], "novel": [46], "joint": [47], "model": [48, 71, 97, 122], "integrates": [50], "recursive": [51], "neural": [52], "networks": [53], "conditional": [55], "random": [56], "fields": [57], "into": [58, 94], "unified": [60], "framework": [61], "explicit": [63], "co-extraction.": [68], "The": [69], "proposed": [70, 96, 121], "learns": [72], "high-level": [73], "discriminative": [74], "features": [75, 93], "double": [77], "propagates": [78], "information": [79, 102], "terms,": [84], "simultaneously.": [85], "Moreover,": [86], "it": [87], "flexible": [89], "to": [90, 98], "incorporate": [91], "hand-crafted": [92], "further": [99], "boost": [100], "its": [101], "extraction": [103], "performance.": [104], "Experimental": [105], "results": [106], "on": [107], "dataset": [109], "SemEval": [111], "Challenge": [112], "2014": [113], "task": [114], "4": [115], "show": [116], "superiority": [118], "our": [120], "over": [123], "several": [124], "baseline": [125], "methods": [126], "as": [127, 129], "well": [128], "winning": [131], "systems": [132], "challenge.": [135]}, "counts_by_year": [{"year": 2026, "cited_by_count": 7}, {"year": 2025, "cited_by_count": 24}, {"year": 2024, "cited_by_count": 23}, {"year": 2023, "cited_by_count": 46}, {"year": 2022, "cited_by_count": 70}, {"year": 2021, "cited_by_count": 64}, {"year": 2020, "cited_by_count": 88}, {"year": 2019, "cited_by_count": 60}, {"year": 2018, "cited_by_count": 22}, {"year": 2017, "cited_by_count": 11}, {"year": 2015, "cited_by_count": 12}], "updated_date": "2026-07-29T14:22:42.915294", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W2116877738", "doi": "https://doi.org/10.1007/s11263-008-0202-0", "title": "Robust Higher Order Potentials for Enforcing Label Consistency", "display_name": "Robust Higher Order Potentials for Enforcing Label Consistency", "relevance_score": 469.88925, "publication_year": 2009, "publication_date": "2009-01-23", "ids": {"openalex": "https://openalex.org/W2116877738", "doi": "https://doi.org/10.1007/s11263-008-0202-0", "mag": "2116877738"}, "language": "en", "primary_location": {"id": "doi:10.1007/s11263-008-0202-0", "is_oa": false, "landing_page_url": "https://doi.org/10.1007/s11263-008-0202-0", "pdf_url": null, "source": {"id": "https://openalex.org/S25538012", "display_name": "International Journal of Computer Vision", "issn_l": "0920-5691", "issn": ["0920-5691", "1573-1405"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310319900", "host_organization_name": "Springer Science+Business Media", "host_organization_lineage": ["https://openalex.org/P4310319900", "https://openalex.org/P4310319965"], "host_organization_lineage_names": ["Springer Science+Business Media", "Springer Nature"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "International Journal of Computer Vision", "raw_type": "journal-article"}, "type": "article", "indexed_in": ["crossref"], "open_access": {"is_oa": true, "oa_status": "green", "oa_url": "https://radar.brookes.ac.uk/radar/file/e70ce935-9726-a58f-650e-e4ffae4709d8/1/kohli2009robust.pdf", "any_repository_has_fulltext": true}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5013834379", "display_name": "Pushmeet Kohli", "orcid": "https://orcid.org/0000-0002-7466-7997"}, "institutions": [{"id": "https://openalex.org/I1290206253", "display_name": "Microsoft (United States)", "ror": "https://ror.org/00d0nc645", "country_code": "US", "type": "company", "lineage": ["https://openalex.org/I1290206253"]}, {"id": "https://openalex.org/I4210164937", "display_name": "Microsoft Research (United Kingdom)", "ror": "https://ror.org/05k87vq12", "country_code": "GB", "type": "company", "lineage": ["https://openalex.org/I1290206253", "https://openalex.org/I4210164937"]}], "countries": ["GB", "US"], "is_corresponding": true, "raw_author_name": "Pushmeet Kohli", "raw_affiliation_strings": ["Microsoft Research, Cambridge, UK", "Microsoft Res. Cambridge, Cambridge, MA"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Microsoft Research, Cambridge, UK", "institution_ids": ["https://openalex.org/I4210164937"]}, {"raw_affiliation_string": "Microsoft Res. Cambridge, Cambridge, MA", "institution_ids": ["https://openalex.org/I1290206253"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5107838703", "display_name": "\u013dubor Ladick\u00fd", "orcid": null}, "institutions": [{"id": "https://openalex.org/I124261462", "display_name": "Oxford Brookes University", "ror": "https://ror.org/04v2twj65", "country_code": "GB", "type": "education", "lineage": ["https://openalex.org/I124261462"]}], "countries": ["GB"], "is_corresponding": false, "raw_author_name": "L\u2019ubor Ladick\u00fd", "raw_affiliation_strings": ["Oxford Brookes University, Oxford, UK", "Oxford Brookes University , UK"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Oxford Brookes University, Oxford, UK", "institution_ids": ["https://openalex.org/I124261462"]}, {"raw_affiliation_string": "Oxford Brookes University , UK", "institution_ids": ["https://openalex.org/I124261462"]}]}, {"author_position": "last", "author": {"id": "https://openalex.org/A5001534492", "display_name": "Philip H. S. Torr", "orcid": null}, "institutions": [{"id": "https://openalex.org/I124261462", "display_name": "Oxford Brookes University", "ror": "https://ror.org/04v2twj65", "country_code": "GB", "type": "education", "lineage": ["https://openalex.org/I124261462"]}], "countries": ["GB"], "is_corresponding": false, "raw_author_name": "Philip H. S. Torr", "raw_affiliation_strings": ["Oxford Brookes University, Oxford, UK", "Oxford Brookes University , UK"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "Oxford Brookes University, Oxford, UK", "institution_ids": ["https://openalex.org/I124261462"]}, {"raw_affiliation_string": "Oxford Brookes University , UK", "institution_ids": ["https://openalex.org/I124261462"]}]}], "institutions": [], "countries_distinct_count": 2, "institutions_distinct_count": 3, "corresponding_author_ids": ["https://openalex.org/A5013834379"], "corresponding_institution_ids": ["https://openalex.org/I1290206253", "https://openalex.org/I4210164937"], "apc_list": {"value": 3690, "currency": "USD", "value_usd": 3690}, "apc_paid": null, "fwci": 62.754, "has_fulltext": true, "cited_by_count": 894, "citation_normalized_percentile": {"value": 0.99948586, "is_in_top_1_percent": true, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 91, "max": 100}, "biblio": {"volume": "82", "issue": "3", "first_page": "302", "last_page": "324"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10036", "display_name": "Advanced Neural Network Applications", "score": 0.998199999332428, "subfield": {"id": "https://openalex.org/subfields/1707", "display_name": "Computer Vision and Pattern Recognition"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10036", "display_name": "Advanced Neural Network Applications", "score": 0.998199999332428, "subfield": {"id": "https://openalex.org/subfields/1707", "display_name": "Computer Vision and Pattern Recognition"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10052", "display_name": "Medical Image Segmentation Techniques", "score": 0.9977999925613403, "subfield": {"id": "https://openalex.org/subfields/1707", "display_name": "Computer Vision and Pattern Recognition"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10627", "display_name": "Advanced Image and Video Retrieval Techniques", "score": 0.9973999857902527, "subfield": {"id": "https://openalex.org/subfields/1707", "display_name": "Computer Vision and Pattern Recognition"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/segmentation", "display_name": "Segmentation", "score": 0.6138601899147034}, {"id": "https://openalex.org/keywords/inference", "display_name": "Inference", "score": 0.5912462472915649}, {"id": "https://openalex.org/keywords/conditional-random-field", "display_name": "Conditional random field", "score": 0.5784097909927368}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.5309911370277405}, {"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.5182116627693176}, {"id": "https://openalex.org/keywords/cut", "display_name": "Cut", "score": 0.5175849199295044}, {"id": "https://openalex.org/keywords/pattern-recognition", "display_name": "Pattern recognition (psychology)", "score": 0.510344922542572}, {"id": "https://openalex.org/keywords/pairwise-comparison", "display_name": "Pairwise comparison", "score": 0.5095779895782471}, {"id": "https://openalex.org/keywords/image-segmentation", "display_name": "Image segmentation", "score": 0.438507616519928}, {"id": "https://openalex.org/keywords/potts-model", "display_name": "Potts model", "score": 0.43034815788269043}, {"id": "https://openalex.org/keywords/pixel", "display_name": "Pixel", "score": 0.4284241795539856}, {"id": "https://openalex.org/keywords/smoothness", "display_name": "Smoothness", "score": 0.414532870054245}, {"id": "https://openalex.org/keywords/mathematics", "display_name": "Mathematics", "score": 0.36617574095726013}, {"id": "https://openalex.org/keywords/algorithm", "display_name": "Algorithm", "score": 0.3400948941707611}], "concepts": [{"id": "https://openalex.org/C89600930", "wikidata": "https://www.wikidata.org/wiki/Q1423946", "display_name": "Segmentation", "level": 2, "score": 0.6138601899147034}, {"id": "https://openalex.org/C2776214188", "wikidata": "https://www.wikidata.org/wiki/Q408386", "display_name": "Inference", "level": 2, "score": 0.5912462472915649}, {"id": "https://openalex.org/C152565575", "wikidata": "https://www.wikidata.org/wiki/Q1124538", "display_name": "Conditional random field", "level": 2, "score": 0.5784097909927368}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.5309911370277405}, {"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.5182116627693176}, {"id": "https://openalex.org/C5134670", "wikidata": "https://www.wikidata.org/wiki/Q1626444", "display_name": "Cut", "level": 4, "score": 0.5175849199295044}, {"id": "https://openalex.org/C153180895", "wikidata": "https://www.wikidata.org/wiki/Q7148389", "display_name": "Pattern recognition (psychology)", "level": 2, "score": 0.510344922542572}, {"id": "https://openalex.org/C184898388", "wikidata": "https://www.wikidata.org/wiki/Q1435712", "display_name": "Pairwise comparison", "level": 2, "score": 0.5095779895782471}, {"id": "https://openalex.org/C124504099", "wikidata": "https://www.wikidata.org/wiki/Q56933", "display_name": "Image segmentation", "level": 3, "score": 0.438507616519928}, {"id": "https://openalex.org/C98925819", "wikidata": "https://www.wikidata.org/wiki/Q7235385", "display_name": "Potts model", "level": 3, "score": 0.43034815788269043}, {"id": "https://openalex.org/C160633673", "wikidata": "https://www.wikidata.org/wiki/Q355198", "display_name": "Pixel", "level": 2, "score": 0.4284241795539856}, {"id": "https://openalex.org/C102634674", "wikidata": "https://www.wikidata.org/wiki/Q868473", "display_name": "Smoothness", "level": 2, "score": 0.414532870054245}, {"id": "https://openalex.org/C33923547", "wikidata": "https://www.wikidata.org/wiki/Q395", "display_name": "Mathematics", "level": 0, "score": 0.36617574095726013}, {"id": "https://openalex.org/C11413529", "wikidata": "https://www.wikidata.org/wiki/Q8366", "display_name": "Algorithm", "level": 1, "score": 0.3400948941707611}, {"id": "https://openalex.org/C134306372", "wikidata": "https://www.wikidata.org/wiki/Q7754", "display_name": "Mathematical analysis", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C51329190", "wikidata": "https://www.wikidata.org/wiki/Q1076349", "display_name": "Ising model", "level": 2, "score": 0.0}, {"id": "https://openalex.org/C121864883", "wikidata": "https://www.wikidata.org/wiki/Q677916", "display_name": "Statistical physics", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C121332964", "wikidata": "https://www.wikidata.org/wiki/Q413", "display_name": "Physics", "level": 0, "score": 0.0}], "mesh": [], "locations_count": 8, "locations": [{"id": "doi:10.1007/s11263-008-0202-0", "is_oa": false, "landing_page_url": "https://doi.org/10.1007/s11263-008-0202-0", "pdf_url": null, "source": {"id": "https://openalex.org/S25538012", "display_name": "International Journal of Computer Vision", "issn_l": "0920-5691", "issn": ["0920-5691", "1573-1405"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310319900", "host_organization_name": "Springer Science+Business Media", "host_organization_lineage": ["https://openalex.org/P4310319900", "https://openalex.org/P4310319965"], "host_organization_lineage_names": ["Springer Science+Business Media", "Springer Nature"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "International Journal of Computer Vision", "raw_type": "journal-article"}, {"id": "pmh:tle:e70ce935-9726-a58f-650e-e4ffae4709d8:b4ef9587-4603-18f8-a471-bb20511f0ad9:1", "is_oa": true, "landing_page_url": "https://radar.brookes.ac.uk/radar/items/e70ce935-9726-a58f-650e-e4ffae4709d8/1", "pdf_url": "https://radar.brookes.ac.uk/radar/file/e70ce935-9726-a58f-650e-e4ffae4709d8/1/kohli2009robust.pdf", "source": {"id": "https://openalex.org/S4306400541", "display_name": "Radar (Oxford Brookes University)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I124261462", "host_organization_name": "Oxford Brookes University", "host_organization_lineage": ["https://openalex.org/I124261462"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "International Journal of Computer Vision", "raw_type": "article"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.187.8646", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.187.8646", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://research.microsoft.com/en-us/um/people/pkohli/papers/klt_IJCV09.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.187.8879", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.187.8879", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://research.microsoft.com/en-us/um/people/pkohli/papers/klt_CVPR08.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.301.1392", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.301.1392", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://cms.brookes.ac.uk/staff/PhilipTorr/Papers/2008/CVPR08/soft_potts.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.320.6543", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.320.6543", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://mplab.ucsd.edu/wp-content/uploads/cvpr2008/conference/data/papers/077.pdf", "raw_type": "text"}, {"id": "pmh:oai:ora.ox.ac.uk:uuid:74b37400-5337-4cca-a4e6-7b34a31de0c1", "is_oa": false, "landing_page_url": null, "pdf_url": null, "source": {"id": "https://openalex.org/S4306402636", "display_name": "Oxford University Research Archive (ORA) (University of Oxford)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I40120149", "host_organization_name": "University of Oxford", "host_organization_lineage": ["https://openalex.org/I40120149"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Symplectic Elements", "raw_type": "Conference item"}, {"id": "pmh:oai:ora.ox.ac.uk:uuid:f5b8b0ce-cb7d-4c41-b10a-dbdc03d813df", "is_oa": false, "landing_page_url": "https://ora.ox.ac.uk/objects/uuid:f5b8b0ce-cb7d-4c41-b10a-dbdc03d813df", "pdf_url": null, "source": {"id": "https://openalex.org/S4306402636", "display_name": "Oxford University Research Archive (ORA) (University of Oxford)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I40120149", "host_organization_name": "University of Oxford", "host_organization_lineage": ["https://openalex.org/I40120149"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Symplectic Elements", "raw_type": "Journal article"}], "best_oa_location": {"id": "pmh:tle:e70ce935-9726-a58f-650e-e4ffae4709d8:b4ef9587-4603-18f8-a471-bb20511f0ad9:1", "is_oa": true, "landing_page_url": "https://radar.brookes.ac.uk/radar/items/e70ce935-9726-a58f-650e-e4ffae4709d8/1", "pdf_url": "https://radar.brookes.ac.uk/radar/file/e70ce935-9726-a58f-650e-e4ffae4709d8/1/kohli2009robust.pdf", "source": {"id": "https://openalex.org/S4306400541", "display_name": "Radar (Oxford Brookes University)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I124261462", "host_organization_name": "Oxford Brookes University", "host_organization_lineage": ["https://openalex.org/I124261462"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "International Journal of Computer Vision", "raw_type": "article"}, "sustainable_development_goals": [{"display_name": "Affordable and clean energy", "score": 0.8500000238418579, "id": "https://metadata.un.org/sdg/7"}], "awards": [], "funders": [{"id": "https://openalex.org/F4320320006", "display_name": "Royal Society", "ror": "https://ror.org/03wnrjx87"}, {"id": "https://openalex.org/F4320320670", "display_name": "Wolfson Foundation", "ror": "https://ror.org/0333xzh65"}, {"id": "https://openalex.org/F4320334627", "display_name": "Engineering and Physical Sciences Research Council", "ror": "https://ror.org/0439y7842"}], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2116877738.pdf", "grobid_xml": "https://content.openalex.org/works/W2116877738.grobid-xml"}, "referenced_works_count": 58, "referenced_works": ["https://openalex.org/W10769007", "https://openalex.org/W59895198", "https://openalex.org/W198996565", "https://openalex.org/W1498671329", "https://openalex.org/W1528789833", "https://openalex.org/W1541388462", "https://openalex.org/W1576820654", "https://openalex.org/W1578197944", "https://openalex.org/W1589208139", "https://openalex.org/W1590899626", "https://openalex.org/W1785730614", "https://openalex.org/W1886770168", "https://openalex.org/W1999478155", "https://openalex.org/W2050511894", "https://openalex.org/W2067191022", "https://openalex.org/W2074078071", "https://openalex.org/W2095844239", "https://openalex.org/W2098678088", "https://openalex.org/W2099835437", "https://openalex.org/W2100824854", "https://openalex.org/W2101309634", "https://openalex.org/W2102621940", "https://openalex.org/W2104125540", "https://openalex.org/W2106110775", "https://openalex.org/W2108619558", "https://openalex.org/W2112301665", "https://openalex.org/W2113206213", "https://openalex.org/W2117435890", "https://openalex.org/W2121845348", "https://openalex.org/W2121947440", "https://openalex.org/W2123282994", "https://openalex.org/W2124351162", "https://openalex.org/W2128680590", "https://openalex.org/W2131686571", "https://openalex.org/W2135165032", "https://openalex.org/W2135968022", "https://openalex.org/W2136224190", "https://openalex.org/W2140502500", "https://openalex.org/W2143516773", "https://openalex.org/W2146036075", "https://openalex.org/W2146369368", "https://openalex.org/W2147880316", "https://openalex.org/W2149203124", "https://openalex.org/W2151996626", "https://openalex.org/W2155871590", "https://openalex.org/W2162366888", "https://openalex.org/W2164918853", "https://openalex.org/W2167008042", "https://openalex.org/W2169551590", "https://openalex.org/W2296770417", "https://openalex.org/W2540072873", "https://openalex.org/W4248635988", "https://openalex.org/W4252621450", "https://openalex.org/W4285719527", "https://openalex.org/W4388323202", "https://openalex.org/W6634563818", "https://openalex.org/W6674866097", "https://openalex.org/W6676044923"], "related_works": ["https://openalex.org/W2356597680", "https://openalex.org/W2093471820", "https://openalex.org/W50079190", "https://openalex.org/W2114846443", "https://openalex.org/W3102147106", "https://openalex.org/W2487162673", "https://openalex.org/W2793211469", "https://openalex.org/W2963336968", "https://openalex.org/W2805329439", "https://openalex.org/W2962748067"], "abstract_inverted_index": null, "counts_by_year": [{"year": 2026, "cited_by_count": 4}, {"year": 2025, "cited_by_count": 1}, {"year": 2024, "cited_by_count": 14}, {"year": 2023, "cited_by_count": 13}, {"year": 2022, "cited_by_count": 15}, {"year": 2021, "cited_by_count": 38}, {"year": 2020, "cited_by_count": 51}, {"year": 2019, "cited_by_count": 50}, {"year": 2018, "cited_by_count": 72}, {"year": 2017, "cited_by_count": 66}, {"year": 2016, "cited_by_count": 98}, {"year": 2015, "cited_by_count": 104}, {"year": 2014, "cited_by_count": 81}, {"year": 2013, "cited_by_count": 86}, {"year": 2012, "cited_by_count": 69}], "updated_date": "2026-07-23T08:03:31.855105", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W3185341429", "doi": "https://doi.org/10.1145/3560815", "title": "Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing", "display_name": "Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing", "relevance_score": 462.1312, "publication_year": 2022, "publication_date": "2022-09-14", "ids": {"openalex": "https://openalex.org/W3185341429", "doi": "https://doi.org/10.1145/3560815", "mag": "3185341429"}, "language": "en", "primary_location": {"id": "doi:10.1145/3560815", "is_oa": true, "landing_page_url": "https://doi.org/10.1145/3560815", "pdf_url": "https://dl.acm.org/doi/pdf/10.1145/3560815", "source": {"id": "https://openalex.org/S157921468", "display_name": "ACM Computing Surveys", "issn_l": "0360-0300", "issn": ["0360-0300", "1557-7341"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310319798", "host_organization_name": "Association for Computing Machinery", "host_organization_lineage": ["https://openalex.org/P4310319798"], "host_organization_lineage_names": ["Association for Computing Machinery"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "ACM Computing Surveys", "raw_type": "journal-article"}, "type": "article", "indexed_in": ["crossref"], "open_access": {"is_oa": true, "oa_status": "bronze", "oa_url": "https://dl.acm.org/doi/pdf/10.1145/3560815", "any_repository_has_fulltext": false}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5100354997", "display_name": "Pengfei Liu", "orcid": "https://orcid.org/0000-0001-9030-1875"}, "institutions": [{"id": "https://openalex.org/I74973139", "display_name": "Carnegie Mellon University", "ror": "https://ror.org/05x2bcf33", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I74973139"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Pengfei Liu", "raw_affiliation_strings": ["Carnegie Mellon University, Pittsburgh, Pennsylvania, USA"], "raw_orcid": "https://orcid.org/0000-0001-9030-1875", "affiliations": [{"raw_affiliation_string": "Carnegie Mellon University, Pittsburgh, Pennsylvania, USA", "institution_ids": ["https://openalex.org/I74973139"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5055933325", "display_name": "Weizhe Yuan", "orcid": "https://orcid.org/0000-0002-6117-9417"}, "institutions": [{"id": "https://openalex.org/I74973139", "display_name": "Carnegie Mellon University", "ror": "https://ror.org/05x2bcf33", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I74973139"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Weizhe Yuan", "raw_affiliation_strings": ["Carnegie Mellon University, Pittsburgh, Pennsylvania, USA"], "raw_orcid": "https://orcid.org/0000-0002-6117-9417", "affiliations": [{"raw_affiliation_string": "Carnegie Mellon University, Pittsburgh, Pennsylvania, USA", "institution_ids": ["https://openalex.org/I74973139"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5103097172", "display_name": "Jinlan Fu", "orcid": "https://orcid.org/0000-0002-0370-1238"}, "institutions": [{"id": "https://openalex.org/I165932596", "display_name": "National University of Singapore", "ror": "https://ror.org/01tgyzw49", "country_code": "SG", "type": "education", "lineage": ["https://openalex.org/I165932596"]}], "countries": ["SG"], "is_corresponding": false, "raw_author_name": "Jinlan Fu", "raw_affiliation_strings": ["National University of Singapore, Singapore"], "raw_orcid": "https://orcid.org/0000-0002-0370-1238", "affiliations": [{"raw_affiliation_string": "National University of Singapore, Singapore", "institution_ids": ["https://openalex.org/I165932596"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5043295774", "display_name": "Zhengbao Jiang", "orcid": "https://orcid.org/0000-0002-0315-6727"}, "institutions": [{"id": "https://openalex.org/I74973139", "display_name": "Carnegie Mellon University", "ror": "https://ror.org/05x2bcf33", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I74973139"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Zhengbao Jiang", "raw_affiliation_strings": ["Carnegie Mellon University, Pittsburgh, Pennsylvania, USA"], "raw_orcid": "https://orcid.org/0000-0002-0315-6727", "affiliations": [{"raw_affiliation_string": "Carnegie Mellon University, Pittsburgh, Pennsylvania, USA", "institution_ids": ["https://openalex.org/I74973139"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5101850869", "display_name": "Hiroaki Hayashi", "orcid": "https://orcid.org/0000-0002-6875-7443"}, "institutions": [{"id": "https://openalex.org/I74973139", "display_name": "Carnegie Mellon University", "ror": "https://ror.org/05x2bcf33", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I74973139"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Hiroaki Hayashi", "raw_affiliation_strings": ["Carnegie Mellon University, Pittsburgh, Pennsylvania, USA"], "raw_orcid": "https://orcid.org/0000-0002-6875-7443", "affiliations": [{"raw_affiliation_string": "Carnegie Mellon University, Pittsburgh, Pennsylvania, USA", "institution_ids": ["https://openalex.org/I74973139"]}]}, {"author_position": "last", "author": {"id": "https://openalex.org/A5068811427", "display_name": "Graham Neubig", "orcid": "https://orcid.org/0000-0002-2072-3789"}, "institutions": [{"id": "https://openalex.org/I74973139", "display_name": "Carnegie Mellon University", "ror": "https://ror.org/05x2bcf33", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I74973139"]}], "countries": ["US"], "is_corresponding": false, "raw_author_name": "Graham Neubig", "raw_affiliation_strings": ["Carnegie Mellon University, Pittsburgh, Pennsylvania, USA"], "raw_orcid": "https://orcid.org/0000-0002-2072-3789", "affiliations": [{"raw_affiliation_string": "Carnegie Mellon University, Pittsburgh, Pennsylvania, USA", "institution_ids": ["https://openalex.org/I74973139"]}]}], "institutions": [], "countries_distinct_count": 2, "institutions_distinct_count": 2, "corresponding_author_ids": [], "corresponding_institution_ids": [], "apc_list": null, "apc_paid": null, "fwci": 383.2022, "has_fulltext": true, "cited_by_count": 3701, "citation_normalized_percentile": {"value": 1.0, "is_in_top_1_percent": true, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 89, "max": 100}, "biblio": {"volume": "55", "issue": "9", "first_page": "1", "last_page": "35"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 1.0, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 1.0, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 0.9997000098228455, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10664", "display_name": "Sentiment Analysis and Opinion Mining", "score": 0.9980000257492065, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.8658277988433838}, {"id": "https://openalex.org/keywords/variety", "display_name": "Variety (cybernetics)", "score": 0.5902861952781677}, {"id": "https://openalex.org/keywords/set", "display_name": "Set (abstract data type)", "score": 0.5378922820091248}, {"id": "https://openalex.org/keywords/notation", "display_name": "Notation", "score": 0.5344952940940857}, {"id": "https://openalex.org/keywords/cover", "display_name": "Cover (algebra)", "score": 0.5327544212341309}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.5117349624633789}, {"id": "https://openalex.org/keywords/natural-language", "display_name": "Natural language", "score": 0.4923027753829956}, {"id": "https://openalex.org/keywords/field", "display_name": "Field (mathematics)", "score": 0.4852149784564972}, {"id": "https://openalex.org/keywords/function", "display_name": "Function (biology)", "score": 0.4821847975254059}, {"id": "https://openalex.org/keywords/language-model", "display_name": "Language model", "score": 0.4774259030818939}, {"id": "https://openalex.org/keywords/string", "display_name": "String (physics)", "score": 0.46483704447746277}, {"id": "https://openalex.org/keywords/natural-language-processing", "display_name": "Natural language processing", "score": 0.4604296386241913}, {"id": "https://openalex.org/keywords/natural-language-understanding", "display_name": "Natural language understanding", "score": 0.4260142147541046}, {"id": "https://openalex.org/keywords/programming-language", "display_name": "Programming language", "score": 0.14141717553138733}, {"id": "https://openalex.org/keywords/linguistics", "display_name": "Linguistics", "score": 0.11886349320411682}], "concepts": [{"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.8658277988433838}, {"id": "https://openalex.org/C136197465", "wikidata": "https://www.wikidata.org/wiki/Q1729295", "display_name": "Variety (cybernetics)", "level": 2, "score": 0.5902861952781677}, {"id": "https://openalex.org/C177264268", "wikidata": "https://www.wikidata.org/wiki/Q1514741", "display_name": "Set (abstract data type)", "level": 2, "score": 0.5378922820091248}, {"id": "https://openalex.org/C45357846", "wikidata": "https://www.wikidata.org/wiki/Q2001982", "display_name": "Notation", "level": 2, "score": 0.5344952940940857}, {"id": "https://openalex.org/C2780428219", "wikidata": "https://www.wikidata.org/wiki/Q16952335", "display_name": "Cover (algebra)", "level": 2, "score": 0.5327544212341309}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.5117349624633789}, {"id": "https://openalex.org/C195324797", "wikidata": "https://www.wikidata.org/wiki/Q33742", "display_name": "Natural language", "level": 2, "score": 0.4923027753829956}, {"id": "https://openalex.org/C9652623", "wikidata": "https://www.wikidata.org/wiki/Q190109", "display_name": "Field (mathematics)", "level": 2, "score": 0.4852149784564972}, {"id": "https://openalex.org/C14036430", "wikidata": "https://www.wikidata.org/wiki/Q3736076", "display_name": "Function (biology)", "level": 2, "score": 0.4821847975254059}, {"id": "https://openalex.org/C137293760", "wikidata": "https://www.wikidata.org/wiki/Q3621696", "display_name": "Language model", "level": 2, "score": 0.4774259030818939}, {"id": "https://openalex.org/C157486923", "wikidata": "https://www.wikidata.org/wiki/Q1376436", "display_name": "String (physics)", "level": 2, "score": 0.46483704447746277}, {"id": "https://openalex.org/C204321447", "wikidata": "https://www.wikidata.org/wiki/Q30642", "display_name": "Natural language processing", "level": 1, "score": 0.4604296386241913}, {"id": "https://openalex.org/C2779439875", "wikidata": "https://www.wikidata.org/wiki/Q1078276", "display_name": "Natural language understanding", "level": 3, "score": 0.4260142147541046}, {"id": "https://openalex.org/C199360897", "wikidata": "https://www.wikidata.org/wiki/Q9143", "display_name": "Programming language", "level": 1, "score": 0.14141717553138733}, {"id": "https://openalex.org/C41895202", "wikidata": "https://www.wikidata.org/wiki/Q8162", "display_name": "Linguistics", "level": 1, "score": 0.11886349320411682}, {"id": "https://openalex.org/C127413603", "wikidata": "https://www.wikidata.org/wiki/Q11023", "display_name": "Engineering", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C138885662", "wikidata": "https://www.wikidata.org/wiki/Q5891", "display_name": "Philosophy", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C33923547", "wikidata": "https://www.wikidata.org/wiki/Q395", "display_name": "Mathematics", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C202444582", "wikidata": "https://www.wikidata.org/wiki/Q837863", "display_name": "Pure mathematics", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C78519656", "wikidata": "https://www.wikidata.org/wiki/Q101333", "display_name": "Mechanical engineering", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C86803240", "wikidata": "https://www.wikidata.org/wiki/Q420", "display_name": "Biology", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C121332964", "wikidata": "https://www.wikidata.org/wiki/Q413", "display_name": "Physics", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C62520636", "wikidata": "https://www.wikidata.org/wiki/Q944", "display_name": "Quantum mechanics", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C78458016", "wikidata": "https://www.wikidata.org/wiki/Q840400", "display_name": "Evolutionary biology", "level": 1, "score": 0.0}], "mesh": [], "locations_count": 1, "locations": [{"id": "doi:10.1145/3560815", "is_oa": true, "landing_page_url": "https://doi.org/10.1145/3560815", "pdf_url": "https://dl.acm.org/doi/pdf/10.1145/3560815", "source": {"id": "https://openalex.org/S157921468", "display_name": "ACM Computing Surveys", "issn_l": "0360-0300", "issn": ["0360-0300", "1557-7341"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310319798", "host_organization_name": "Association for Computing Machinery", "host_organization_lineage": ["https://openalex.org/P4310319798"], "host_organization_lineage_names": ["Association for Computing Machinery"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "ACM Computing Surveys", "raw_type": "journal-article"}], "best_oa_location": {"id": "doi:10.1145/3560815", "is_oa": true, "landing_page_url": "https://doi.org/10.1145/3560815", "pdf_url": "https://dl.acm.org/doi/pdf/10.1145/3560815", "source": {"id": "https://openalex.org/S157921468", "display_name": "ACM Computing Surveys", "issn_l": "0360-0300", "issn": ["0360-0300", "1557-7341"], "is_oa": false, "is_in_doaj": false, "is_core": true, "host_organization": "https://openalex.org/P4310319798", "host_organization_name": "Association for Computing Machinery", "host_organization_lineage": ["https://openalex.org/P4310319798"], "host_organization_lineage_names": ["Association for Computing Machinery"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "ACM Computing Surveys", "raw_type": "journal-article"}, "sustainable_development_goals": [{"display_name": "Quality Education", "score": 0.8299999833106995, "id": "https://metadata.un.org/sdg/4"}], "awards": [], "funders": [], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W3185341429.pdf", "grobid_xml": "https://content.openalex.org/works/W3185341429.grobid-xml"}, "referenced_works_count": 120, "referenced_works": ["https://openalex.org/W102110531", "https://openalex.org/W1832693441", "https://openalex.org/W1873332500", "https://openalex.org/W1934890906", "https://openalex.org/W1982795016", "https://openalex.org/W2064675550", "https://openalex.org/W2083735344", "https://openalex.org/W2100128988", "https://openalex.org/W2120615054", "https://openalex.org/W2121863487", "https://openalex.org/W2130774920", "https://openalex.org/W2143426320", "https://openalex.org/W2143612262", "https://openalex.org/W2163922914", "https://openalex.org/W2166706824", "https://openalex.org/W2250225488", "https://openalex.org/W2250539671", "https://openalex.org/W2467834614", "https://openalex.org/W2510850444", "https://openalex.org/W2524182563", "https://openalex.org/W2559655401", "https://openalex.org/W2560674852", "https://openalex.org/W2598654328", "https://openalex.org/W2601450892", "https://openalex.org/W2606964149", "https://openalex.org/W2608239929", "https://openalex.org/W2610850660", "https://openalex.org/W2612690371", "https://openalex.org/W2739918945", "https://openalex.org/W2744813330", "https://openalex.org/W2759653627", "https://openalex.org/W2771472444", "https://openalex.org/W2796032388", "https://openalex.org/W2798542795", "https://openalex.org/W2809324505", "https://openalex.org/W2948468976", "https://openalex.org/W2950645060", "https://openalex.org/W2952984539", "https://openalex.org/W2962739339", "https://openalex.org/W2962805889", "https://openalex.org/W2962833140", "https://openalex.org/W2962902328", "https://openalex.org/W2963018920", "https://openalex.org/W2963026768", "https://openalex.org/W2963104691", "https://openalex.org/W2963216553", "https://openalex.org/W2963341956", "https://openalex.org/W2963609889", "https://openalex.org/W2963630207", "https://openalex.org/W2963705779", "https://openalex.org/W2963748441", "https://openalex.org/W2963963993", "https://openalex.org/W2964222246", "https://openalex.org/W2965373594", "https://openalex.org/W2970161131", "https://openalex.org/W2970200208", "https://openalex.org/W2970352191", "https://openalex.org/W2970476646", "https://openalex.org/W2970780738", "https://openalex.org/W2973519210", "https://openalex.org/W2981852735", "https://openalex.org/W2982756474", "https://openalex.org/W2986266667", "https://openalex.org/W2989911337", "https://openalex.org/W2990138404", "https://openalex.org/W2997617958", "https://openalex.org/W3004346089", "https://openalex.org/W3005700362", "https://openalex.org/W3007672467", "https://openalex.org/W3013444301", "https://openalex.org/W3034797437", "https://openalex.org/W3034942609", "https://openalex.org/W3034999214", "https://openalex.org/W3035625205", "https://openalex.org/W3041498386", "https://openalex.org/W3044438666", "https://openalex.org/W3092288641", "https://openalex.org/W3092785544", "https://openalex.org/W3096580779", "https://openalex.org/W3098267758", "https://openalex.org/W3098341425", "https://openalex.org/W3099655892", "https://openalex.org/W3099771192", "https://openalex.org/W3102187933", "https://openalex.org/W3104163040", "https://openalex.org/W3104597016", "https://openalex.org/W3122241445", "https://openalex.org/W3141940864", "https://openalex.org/W3153427360", "https://openalex.org/W3153451655", "https://openalex.org/W3154903254", "https://openalex.org/W3156012351", "https://openalex.org/W3156470785", "https://openalex.org/W3160638507", "https://openalex.org/W3166846774", "https://openalex.org/W3166986030", "https://openalex.org/W3167602185", "https://openalex.org/W3170083118", "https://openalex.org/W3170658419", "https://openalex.org/W3172642864", "https://openalex.org/W3173617765", "https://openalex.org/W3173777717", "https://openalex.org/W3174770825", "https://openalex.org/W3174784402", "https://openalex.org/W3175603587", "https://openalex.org/W3176549752", "https://openalex.org/W3182696977", "https://openalex.org/W3194836374", "https://openalex.org/W3199958362", "https://openalex.org/W3211848854", "https://openalex.org/W3212893438", "https://openalex.org/W4205857304", "https://openalex.org/W4205991051", "https://openalex.org/W4206636317", "https://openalex.org/W4225590069", "https://openalex.org/W4287867774", "https://openalex.org/W4288089799", "https://openalex.org/W4293350112", "https://openalex.org/W6735236233", "https://openalex.org/W6964124353"], "related_works": ["https://openalex.org/W2049117375", "https://openalex.org/W3015724364", "https://openalex.org/W4288263119", "https://openalex.org/W2967994095", "https://openalex.org/W2900126711", "https://openalex.org/W4285240985", "https://openalex.org/W4225162083", "https://openalex.org/W2542958340", "https://openalex.org/W3202115945", "https://openalex.org/W4286930972"], "abstract_inverted_index": {"This": [0, 115], "article": [1], "surveys": [2], "and": [3, 34, 86, 119, 140, 195, 210, 232, 253], "organizes": [4], "research": [5], "works": [6, 231], "in": [7, 11, 30], "a": [8, 26, 73, 76, 101, 122, 143, 180, 189, 226, 233, 246], "new": [9, 144, 160], "paradigm": [10], "natural": [12], "language": [13, 49, 89, 129, 207], "processing,": [14], "which": [15, 24, 107], "we": [16, 171, 222], "dub": [17], "\u201cprompt-based": [18], "learning.\u201d": [19], "Unlike": [20], "traditional": [21], "supervised": [22], "learning,": [23, 157], "trains": [25], "model": [27, 52, 90, 130, 148], "to": [28, 62, 93, 99, 131, 151, 159, 219], "take": [29], "an": [31, 36], "input": [32, 68], "x": [33, 69], "predict": [35], "output": [37, 110], "y": [38, 111], "as": [39], "P": [40], "(": [41], "y|x": [42], "),": [43], "prompt-based": [44, 238], "learning": [45], "is": [46, 70, 91, 117, 149], "based": [47], "on": [48, 134], "models": [50, 61], "that": [51, 81, 186], "the": [53, 66, 88, 96, 108, 128, 147, 173, 203, 215], "probability": [54], "of": [55, 124, 137, 175, 183, 192, 205, 229, 237], "text": [56], "directly.": [57], "To": [58, 213], "use": [59], "these": [60], "perform": [63, 152], "prediction": [64], "tasks,": [65], "original": [67], "modified": [71], "using": [72], "template": [74], "into": [75], "textual": [77], "string": [78, 103], "prompt": [79], "x\u2032": [80], "has": [82], "some": [83], "unfilled": [84, 97], "slots,": [85], "then": [87], "used": [92], "probabilistically": [94], "fill": [95], "information": [98], "obtain": [100], "final": [102, 109], "x\u0302": [104], ",": [105], "from": [106], "can": [112, 187], "be": [113, 132], "derived.": [114], "framework": [116], "powerful": [118], "attractive": [120], "for": [121], "number": [123], "reasons:": [125], "It": [126], "allows": [127], "pre-trained": [133, 206], "massive": [135], "amounts": [136], "raw": [138], "text,": [139], "by": [141], "defining": [142], "prompting": [145], "function": [146], "able": [150], "few-shot": [153], "or": [154, 164], "even": [155], "zero-shot": [156], "adapting": [158], "scenarios": [161], "with": [162], "few": [163], "no": [165], "labeled": [166], "data.": [167], "In": [168], "this": [169, 176], "article,": [170], "introduce": [172], "basics": [174], "promising": [177], "paradigm,": [178], "describe": [179], "unified": [181], "set": [182], "mathematical": [184], "notations": [185], "cover": [188], "wide": [190], "variety": [191], "existing": [193, 197, 230], "work,": [194], "organize": [196], "work": [198], "along": [199], "several": [200], "dimensions,": [201], "e.g.,": [202, 245], "choice": [204], "models,": [208], "prompts,": [209], "tuning": [211], "strategies.": [212], "make": [214, 225], "field": [216], "more": [217], "accessible": [218], "interested": [220], "beginners,": [221], "not": [223], "only": [224], "systematic": [227], "review": [228], "highly": [234], "structured": [235], "typology": [236], "concepts": [239], "but": [240], "also": [241], "release": [242], "other": [243], "resources,": [244], "website": [247], "NLPedia\u2013Pretrain": [248], "including": [249], "constantly": [250], "updated": [251], "survey": [252], "paperlist.": [254]}, "counts_by_year": [{"year": 2026, "cited_by_count": 371}, {"year": 2025, "cited_by_count": 1227}, {"year": 2024, "cited_by_count": 1205}, {"year": 2023, "cited_by_count": 769}, {"year": 2022, "cited_by_count": 97}, {"year": 2021, "cited_by_count": 31}, {"year": 2020, "cited_by_count": 1}], "updated_date": "2026-08-06T08:24:18.245995", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W2092654472", "doi": "https://doi.org/10.1162/089120103322753356", "title": "Head-Driven Statistical Models for Natural Language Parsing", "display_name": "Head-Driven Statistical Models for Natural Language Parsing", "relevance_score": 454.45966, "publication_year": 2003, "publication_date": "2003-12-01", "ids": {"openalex": "https://openalex.org/W2092654472", "doi": "https://doi.org/10.1162/089120103322753356", "mag": "2092654472"}, "language": "en", "primary_location": {"id": "doi:10.1162/089120103322753356", "is_oa": true, "landing_page_url": "https://doi.org/10.1162/089120103322753356", "pdf_url": "http://www.mitpressjournals.org/doi/pdf/10.1162/089120103322753356", "source": {"id": "https://openalex.org/S155526855", "display_name": "Computational Linguistics", "issn_l": "0891-2017", "issn": ["0891-2017", "1530-9312"], "is_oa": false, "is_in_doaj": true, "is_core": true, "host_organization": "https://openalex.org/P4310320244", "host_organization_name": "Association for Computational Linguistics", "host_organization_lineage": ["https://openalex.org/P4310320244"], "host_organization_lineage_names": ["Association for Computational Linguistics"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Computational Linguistics", "raw_type": "journal-article"}, "type": "article", "indexed_in": ["crossref", "doaj"], "open_access": {"is_oa": true, "oa_status": "bronze", "oa_url": "http://www.mitpressjournals.org/doi/pdf/10.1162/089120103322753356", "any_repository_has_fulltext": false}, "authorships": [{"author_position": "first", "author": {"id": "https://openalex.org/A5079061237", "display_name": "Michael Collins", "orcid": "https://orcid.org/0000-0003-0997-1527"}, "institutions": [{"id": "https://openalex.org/I63966007", "display_name": "Massachusetts Institute of Technology", "ror": "https://ror.org/042nb2s44", "country_code": "US", "type": "education", "lineage": ["https://openalex.org/I63966007"]}], "countries": ["US"], "is_corresponding": true, "raw_author_name": "Michael Collins", "raw_affiliation_strings": ["MIT Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 545 Technology Square, Cambridge, MA 02139", "MIT Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 545 Technology Square, Cambridge, MA 02139. E-mail:"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "MIT Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 545 Technology Square, Cambridge, MA 02139", "institution_ids": ["https://openalex.org/I63966007"]}, {"raw_affiliation_string": "MIT Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 545 Technology Square, Cambridge, MA 02139. E-mail:", "institution_ids": ["https://openalex.org/I63966007"]}]}], "institutions": [], "countries_distinct_count": 1, "institutions_distinct_count": 1, "corresponding_author_ids": ["https://openalex.org/A5079061237"], "corresponding_institution_ids": ["https://openalex.org/I63966007"], "apc_list": null, "apc_paid": null, "fwci": 247.157, "has_fulltext": true, "cited_by_count": 1861, "citation_normalized_percentile": {"value": 0.99996058, "is_in_top_1_percent": true, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 96, "max": 100}, "biblio": {"volume": "29", "issue": "4", "first_page": "589", "last_page": "637"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 1.0, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, "topics": [{"id": "https://openalex.org/T10181", "display_name": "Natural Language Processing Techniques", "score": 1.0, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.9997000098228455, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}, {"id": "https://openalex.org/T11269", "display_name": "Algorithms and Data Compression", "score": 0.994700014591217, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.8670885562896729}, {"id": "https://openalex.org/keywords/treebank", "display_name": "Treebank", "score": 0.8610374927520752}, {"id": "https://openalex.org/keywords/bigram", "display_name": "Bigram", "score": 0.7364609241485596}, {"id": "https://openalex.org/keywords/natural-language-processing", "display_name": "Natural language processing", "score": 0.7330614328384399}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.7075300216674805}, {"id": "https://openalex.org/keywords/parsing", "display_name": "Parsing", "score": 0.7041088938713074}, {"id": "https://openalex.org/keywords/probabilistic-logic", "display_name": "Probabilistic logic", "score": 0.4779134690761566}, {"id": "https://openalex.org/keywords/natural-language-understanding", "display_name": "Natural language understanding", "score": 0.4770828187465668}, {"id": "https://openalex.org/keywords/natural-language", "display_name": "Natural language", "score": 0.46837741136550903}, {"id": "https://openalex.org/keywords/rule-based-machine-translation", "display_name": "Rule-based machine translation", "score": 0.4459387958049774}, {"id": "https://openalex.org/keywords/trigram", "display_name": "Trigram", "score": 0.11375659704208374}], "concepts": [{"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.8670885562896729}, {"id": "https://openalex.org/C206134035", "wikidata": "https://www.wikidata.org/wiki/Q811525", "display_name": "Treebank", "level": 3, "score": 0.8610374927520752}, {"id": "https://openalex.org/C108757681", "wikidata": "https://www.wikidata.org/wiki/Q2773912", "display_name": "Bigram", "level": 3, "score": 0.7364609241485596}, {"id": "https://openalex.org/C204321447", "wikidata": "https://www.wikidata.org/wiki/Q30642", "display_name": "Natural language processing", "level": 1, "score": 0.7330614328384399}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.7075300216674805}, {"id": "https://openalex.org/C186644900", "wikidata": "https://www.wikidata.org/wiki/Q194152", "display_name": "Parsing", "level": 2, "score": 0.7041088938713074}, {"id": "https://openalex.org/C49937458", "wikidata": "https://www.wikidata.org/wiki/Q2599292", "display_name": "Probabilistic logic", "level": 2, "score": 0.4779134690761566}, {"id": "https://openalex.org/C2779439875", "wikidata": "https://www.wikidata.org/wiki/Q1078276", "display_name": "Natural language understanding", "level": 3, "score": 0.4770828187465668}, {"id": "https://openalex.org/C195324797", "wikidata": "https://www.wikidata.org/wiki/Q33742", "display_name": "Natural language", "level": 2, "score": 0.46837741136550903}, {"id": "https://openalex.org/C53893814", "wikidata": "https://www.wikidata.org/wiki/Q7378909", "display_name": "Rule-based machine translation", "level": 2, "score": 0.4459387958049774}, {"id": "https://openalex.org/C137546455", "wikidata": "https://www.wikidata.org/wiki/Q3213474", "display_name": "Trigram", "level": 2, "score": 0.11375659704208374}], "mesh": [], "locations_count": 6, "locations": [{"id": "doi:10.1162/089120103322753356", "is_oa": true, "landing_page_url": "https://doi.org/10.1162/089120103322753356", "pdf_url": "http://www.mitpressjournals.org/doi/pdf/10.1162/089120103322753356", "source": {"id": "https://openalex.org/S155526855", "display_name": "Computational Linguistics", "issn_l": "0891-2017", "issn": ["0891-2017", "1530-9312"], "is_oa": false, "is_in_doaj": true, "is_core": true, "host_organization": "https://openalex.org/P4310320244", "host_organization_name": "Association for Computational Linguistics", "host_organization_lineage": ["https://openalex.org/P4310320244"], "host_organization_lineage_names": ["Association for Computational Linguistics"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Computational Linguistics", "raw_type": "journal-article"}, {"id": "pmh:oai:repository.upenn.edu:dissertations-1896", "is_oa": false, "landing_page_url": "https://repository.upenn.edu/dissertations/AAI9926110", "pdf_url": null, "source": {"id": "https://openalex.org/S4377196331", "display_name": "Scholarly Commons (University of Pennsylvania)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": "https://openalex.org/I79576946", "host_organization_name": "University of Pennsylvania", "host_organization_lineage": ["https://openalex.org/I79576946"], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Dissertations available from ProQuest", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.416.3677", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.416.3677", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.public.asu.edu/~jzhou29/MLNLP/papers/zettlemoyer/dissertation/Michael Collins-thesis.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.5.5668", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.5.5668", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://acl.ldc.upenn.edu/J/J03/J03-4003.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.57.9525", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.57.9525", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.ai.mit.edu/people/mcollins/papers/CL2003.ps", "raw_type": "text"}, {"id": "pmh:oai:doaj.org/article:bae78c9ab99a418db69c53e4b2a25a4e", "is_oa": false, "landing_page_url": "https://doaj.org/article/bae78c9ab99a418db69c53e4b2a25a4e", "pdf_url": null, "source": {"id": "https://openalex.org/S4306401280", "display_name": "DOAJ (DOAJ: Directory of Open Access Journals)", "issn_l": null, "issn": null, "is_oa": false, "is_in_doaj": false, "is_core": false, "host_organization": null, "host_organization_name": null, "host_organization_lineage": [], "host_organization_lineage_names": [], "type": "repository"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Computational Linguistics, Vol 29, Iss 4 (2021)", "raw_type": "article"}], "best_oa_location": {"id": "doi:10.1162/089120103322753356", "is_oa": true, "landing_page_url": "https://doi.org/10.1162/089120103322753356", "pdf_url": "http://www.mitpressjournals.org/doi/pdf/10.1162/089120103322753356", "source": {"id": "https://openalex.org/S155526855", "display_name": "Computational Linguistics", "issn_l": "0891-2017", "issn": ["0891-2017", "1530-9312"], "is_oa": false, "is_in_doaj": true, "is_core": true, "host_organization": "https://openalex.org/P4310320244", "host_organization_name": "Association for Computational Linguistics", "host_organization_lineage": ["https://openalex.org/P4310320244"], "host_organization_lineage_names": ["Association for Computational Linguistics"], "type": "journal"}, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Computational Linguistics", "raw_type": "journal-article"}, "sustainable_development_goals": [{"display_name": "Quality Education", "score": 0.8500000238418579, "id": "https://metadata.un.org/sdg/4"}], "awards": [], "funders": [], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2092654472.pdf", "grobid_xml": "https://content.openalex.org/works/W2092654472.grobid-xml"}, "referenced_works_count": 63, "referenced_works": ["https://openalex.org/W79411081", "https://openalex.org/W131829211", "https://openalex.org/W199541590", "https://openalex.org/W1491745322", "https://openalex.org/W1508191042", "https://openalex.org/W1509045587", "https://openalex.org/W1535015163", "https://openalex.org/W1567570606", "https://openalex.org/W1574901103", "https://openalex.org/W1585559843", "https://openalex.org/W1598003989", "https://openalex.org/W1600844763", "https://openalex.org/W1601728146", "https://openalex.org/W1632114991", "https://openalex.org/W1773803948", "https://openalex.org/W1809152426", "https://openalex.org/W1936920915", "https://openalex.org/W1972573551", "https://openalex.org/W1982944197", "https://openalex.org/W1986543644", "https://openalex.org/W1993750641", "https://openalex.org/W1994507518", "https://openalex.org/W2002089154", "https://openalex.org/W2004673890", "https://openalex.org/W2005505724", "https://openalex.org/W2039240651", "https://openalex.org/W2052449326", "https://openalex.org/W2069912724", "https://openalex.org/W2074260075", "https://openalex.org/W2077613835", "https://openalex.org/W2087165009", "https://openalex.org/W2093647425", "https://openalex.org/W2096466920", "https://openalex.org/W2102924265", "https://openalex.org/W2104029044", "https://openalex.org/W2104399512", "https://openalex.org/W2110607519", "https://openalex.org/W2110651511", "https://openalex.org/W2110882317", "https://openalex.org/W2111041233", "https://openalex.org/W2113641473", "https://openalex.org/W2114886551", "https://openalex.org/W2123893795", "https://openalex.org/W2134666210", "https://openalex.org/W2138389163", "https://openalex.org/W2139895384", "https://openalex.org/W2147880316", "https://openalex.org/W2153439141", "https://openalex.org/W2155693943", "https://openalex.org/W2161160885", "https://openalex.org/W2163918411", "https://openalex.org/W2166451556", "https://openalex.org/W2167434254", "https://openalex.org/W2309755354", "https://openalex.org/W2949237929", "https://openalex.org/W2952654140", "https://openalex.org/W2963847008", "https://openalex.org/W3021452258", "https://openalex.org/W3021713638", "https://openalex.org/W3088560083", "https://openalex.org/W4231741839", "https://openalex.org/W4241850027", "https://openalex.org/W4285719527"], "related_works": ["https://openalex.org/W1523666900", "https://openalex.org/W2367925007", "https://openalex.org/W3015724364", "https://openalex.org/W4288263119", "https://openalex.org/W2967994095", "https://openalex.org/W2900126711", "https://openalex.org/W4285240985", "https://openalex.org/W4225162083", "https://openalex.org/W3202115945", "https://openalex.org/W2542958340"], "abstract_inverted_index": {"This": [0], "article": [1], "describes": [2], "three": [3], "statistical": [4], "models": [5, 11, 85, 103, 143, 167], "for": [6, 69], "natural": [7], "language": [8], "parsing.": [9], "The": [10, 84], "extend": [12], "methods": [13], "from": [14], "probabilistic": [15], "context-free": [16], "grammars": [17], "to": [18, 22, 37, 49, 168, 174, 179], "lexicalized": [19], "grammars,": [20], "leading": [21], "approaches": [23], "in": [24, 104, 131, 155, 186], "which": [25], "a": [26, 38, 109, 126], "parse": [27], "tree": [28], "is": [29, 99], "represented": [30], "as": [31, 123, 125], "the": [32, 43, 53, 89, 105, 113, 142, 156, 166, 176, 184, 189], "sequence": [33], "of": [34, 42, 58, 61, 73, 112, 128, 135, 141, 152, 183, 188], "decisions": [35], "corresponding": [36], "head-centered,": [39], "top-down": [40], "derivation": [41], "tree.": [44], "Independence": [45], "assumptions": [46], "then": [47], "lead": [48], "parameters": [50], "that": [51, 96, 170], "encode": [52], "X-bar": [54], "schema,": [55], "subcategorization,": [56], "ordering": [57], "complements,": [59], "placement": [60], "adjuncts,": [62], "bigram": [63], "lexical": [64, 82], "dependencies,": [65], "wh-movement,": [66], "and": [67, 158], "preferences": [68, 75], "close": [70], "attachment.": [71], "All": [72], "these": [74], "are": [76, 86], "expressed": [77], "by": [78, 149], "probabilities": [79], "conditioned": [80], "on": [81, 88, 119, 146], "heads.": [83], "evaluated": [87], "Penn": [90], "Wall": [91], "Street": [92], "Journal": [93], "Treebank,": [94], "showing": [95], "their": [97], "accuracy": [98], "competitive": [100], "with": [101], "other": [102], "literature.": [106], "To": [107], "gain": [108], "better": [110], "understanding": [111], "models,": [114], "we": [115, 164], "also": [116], "give": [117, 180], "results": [118, 130], "different": [120], "constituent": [121], "types,": [122], "well": [124], "breakdown": [127], "precision/recall": [129], "recovering": [132], "various": [133, 139, 153, 190], "types": [134], "dependencies.": [136], "We": [137], "analyze": [138], "characteristics": [140], "through": [144, 159], "experiments": [145], "parsing": [147, 175], "accuracy,": [148], "collecting": [150], "frequencies": [151], "structures": [154], "treebank,": [157, 177], "linguistically": [160], "motivated": [161], "examples.": [162], "Finally,": [163], "compare": [165], "others": [169], "have": [171], "been": [172], "applied": [173], "aiming": [178], "some": [181], "explanation": [182], "difference": [185], "performance": [187], "models.": [191]}, "counts_by_year": [{"year": 2025, "cited_by_count": 8}, {"year": 2024, "cited_by_count": 3}, {"year": 2023, "cited_by_count": 8}, {"year": 2022, "cited_by_count": 14}, {"year": 2021, "cited_by_count": 23}, {"year": 2020, "cited_by_count": 22}, {"year": 2019, "cited_by_count": 46}, {"year": 2018, "cited_by_count": 34}, {"year": 2017, "cited_by_count": 43}, {"year": 2016, "cited_by_count": 52}, {"year": 2015, "cited_by_count": 68}, {"year": 2014, "cited_by_count": 83}, {"year": 2013, "cited_by_count": 141}, {"year": 2012, "cited_by_count": 96}], "updated_date": "2026-08-01T09:00:35.917206", "created_date": "2025-10-10T00:00:00"}, {"id": "https://openalex.org/W2150969560", "doi": "https://doi.org/10.3115/1220175.1220202", "title": "Semi-supervised conditional random fields for improved sequence segmentation and labeling", "display_name": "Semi-supervised conditional random fields for improved sequence segmentation and labeling", "relevance_score": 446.38333, "publication_year": 2006, "publication_date": "2006-01-01", "ids": {"openalex": "https://openalex.org/W2150969560", "doi": "https://doi.org/10.3115/1220175.1220202", "mag": "2150969560"}, "language": "en", "primary_location": {"id": "doi:10.3115/1220175.1220202", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1220175.1220202", "pdf_url": "https://dl.acm.org/doi/pdf/10.3115/1220175.1220202", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the ACL - ACL '06", "raw_type": "proceedings-article"}, "type": "conference-paper", "indexed_in": ["crossref"], "open_access": {"is_oa": true, "oa_status": "gold", "oa_url": "https://dl.acm.org/doi/pdf/10.3115/1220175.1220202", "any_repository_has_fulltext": null}, "authorships": [{"author_position": "first", "author": {"id": null, "display_name": "Feng Jiao", "orcid": null}, "institutions": [{"id": "https://openalex.org/I151746483", "display_name": "University of Waterloo", "ror": "https://ror.org/01aff2v68", "country_code": "CA", "type": "education", "lineage": ["https://openalex.org/I151746483"]}], "countries": ["CA"], "is_corresponding": false, "raw_author_name": "Feng Jiao", "raw_affiliation_strings": ["University of Waterloo"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Waterloo", "institution_ids": ["https://openalex.org/I151746483"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5100702016", "display_name": "Shaojun Wang", "orcid": "https://orcid.org/0000-0003-0467-8911"}, "institutions": [{"id": "https://openalex.org/I154425047", "display_name": "University of Alberta", "ror": "https://ror.org/0160cpw27", "country_code": "CA", "type": "education", "lineage": ["https://openalex.org/I154425047"]}], "countries": ["CA"], "is_corresponding": false, "raw_author_name": "Shaojun Wang", "raw_affiliation_strings": ["University of Alberta"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Alberta", "institution_ids": ["https://openalex.org/I154425047"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5102857306", "display_name": "Chi\u2010Hoon Lee", "orcid": "https://orcid.org/0000-0003-2165-9421"}, "institutions": [{"id": "https://openalex.org/I154425047", "display_name": "University of Alberta", "ror": "https://ror.org/0160cpw27", "country_code": "CA", "type": "education", "lineage": ["https://openalex.org/I154425047"]}], "countries": ["CA"], "is_corresponding": false, "raw_author_name": "Chi-Hoon Lee", "raw_affiliation_strings": ["University of Alberta"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Alberta", "institution_ids": ["https://openalex.org/I154425047"]}]}, {"author_position": "middle", "author": {"id": "https://openalex.org/A5027200864", "display_name": "Russell Greiner", "orcid": "https://orcid.org/0000-0001-8327-934X"}, "institutions": [{"id": "https://openalex.org/I154425047", "display_name": "University of Alberta", "ror": "https://ror.org/0160cpw27", "country_code": "CA", "type": "education", "lineage": ["https://openalex.org/I154425047"]}], "countries": ["CA"], "is_corresponding": false, "raw_author_name": "Russell Greiner", "raw_affiliation_strings": ["University of Alberta"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Alberta", "institution_ids": ["https://openalex.org/I154425047"]}]}, {"author_position": "last", "author": {"id": "https://openalex.org/A5010575626", "display_name": "Dale Schuurmans", "orcid": null}, "institutions": [{"id": "https://openalex.org/I154425047", "display_name": "University of Alberta", "ror": "https://ror.org/0160cpw27", "country_code": "CA", "type": "education", "lineage": ["https://openalex.org/I154425047"]}], "countries": ["CA"], "is_corresponding": false, "raw_author_name": "Dale Schuurmans", "raw_affiliation_strings": ["University of Alberta"], "raw_orcid": null, "affiliations": [{"raw_affiliation_string": "University of Alberta", "institution_ids": ["https://openalex.org/I154425047"]}]}], "institutions": [], "countries_distinct_count": 1, "institutions_distinct_count": 2, "corresponding_author_ids": [], "corresponding_institution_ids": [], "apc_list": null, "apc_paid": null, "fwci": 26.6777, "has_fulltext": true, "cited_by_count": 130, "citation_normalized_percentile": {"value": 0.99806086, "is_in_top_1_percent": true, "is_in_top_10_percent": true}, "cited_by_percentile_year": {"min": 89, "max": 100}, "biblio": {"volume": null, "issue": null, "first_page": "209", "last_page": "216"}, "is_retracted": false, "is_paratext": false, "is_xpac": false, "primary_topic": {"id": "https://openalex.org/T12254", "display_name": "Machine Learning in Bioinformatics", "score": 0.9986000061035156, "subfield": {"id": "https://openalex.org/subfields/1312", "display_name": "Molecular Biology"}, "field": {"id": "https://openalex.org/fields/13", "display_name": "Biochemistry, Genetics and Molecular Biology"}, "domain": {"id": "https://openalex.org/domains/1", "display_name": "Life Sciences"}}, "topics": [{"id": "https://openalex.org/T12254", "display_name": "Machine Learning in Bioinformatics", "score": 0.9986000061035156, "subfield": {"id": "https://openalex.org/subfields/1312", "display_name": "Molecular Biology"}, "field": {"id": "https://openalex.org/fields/13", "display_name": "Biochemistry, Genetics and Molecular Biology"}, "domain": {"id": "https://openalex.org/domains/1", "display_name": "Life Sciences"}}, {"id": "https://openalex.org/T10015", "display_name": "Genomics and Phylogenetic Studies", "score": 0.9912999868392944, "subfield": {"id": "https://openalex.org/subfields/1312", "display_name": "Molecular Biology"}, "field": {"id": "https://openalex.org/fields/13", "display_name": "Biochemistry, Genetics and Molecular Biology"}, "domain": {"id": "https://openalex.org/domains/1", "display_name": "Life Sciences"}}, {"id": "https://openalex.org/T10028", "display_name": "Topic Modeling", "score": 0.982200026512146, "subfield": {"id": "https://openalex.org/subfields/1702", "display_name": "Artificial Intelligence"}, "field": {"id": "https://openalex.org/fields/17", "display_name": "Computer Science"}, "domain": {"id": "https://openalex.org/domains/3", "display_name": "Physical Sciences"}}], "keywords": [{"id": "https://openalex.org/keywords/conditional-random-field", "display_name": "Conditional random field", "score": 0.95069819688797}, {"id": "https://openalex.org/keywords/crfs", "display_name": "CRFS", "score": 0.8853049874305725}, {"id": "https://openalex.org/keywords/conditional-entropy", "display_name": "Conditional entropy", "score": 0.8247196078300476}, {"id": "https://openalex.org/keywords/sequence-labeling", "display_name": "Sequence labeling", "score": 0.7765474915504456}, {"id": "https://openalex.org/keywords/computer-science", "display_name": "Computer science", "score": 0.656731128692627}, {"id": "https://openalex.org/keywords/artificial-intelligence", "display_name": "Artificial intelligence", "score": 0.6271525621414185}, {"id": "https://openalex.org/keywords/entropy", "display_name": "Entropy (arrow of time)", "score": 0.5572037100791931}, {"id": "https://openalex.org/keywords/machine-learning", "display_name": "Machine learning", "score": 0.5383710861206055}, {"id": "https://openalex.org/keywords/regularization", "display_name": "Regularization (linguistics)", "score": 0.5360749959945679}, {"id": "https://openalex.org/keywords/structured-prediction", "display_name": "Structured prediction", "score": 0.4671812653541565}, {"id": "https://openalex.org/keywords/segmentation", "display_name": "Segmentation", "score": 0.44676434993743896}, {"id": "https://openalex.org/keywords/pattern-recognition", "display_name": "Pattern recognition (psychology)", "score": 0.44383111596107483}, {"id": "https://openalex.org/keywords/cross-entropy", "display_name": "Cross entropy", "score": 0.443760484457016}, {"id": "https://openalex.org/keywords/principle-of-maximum-entropy", "display_name": "Principle of maximum entropy", "score": 0.37270182371139526}], "concepts": [{"id": "https://openalex.org/C152565575", "wikidata": "https://www.wikidata.org/wiki/Q1124538", "display_name": "Conditional random field", "level": 2, "score": 0.95069819688797}, {"id": "https://openalex.org/C2775953691", "wikidata": "https://www.wikidata.org/wiki/Q5013874", "display_name": "CRFS", "level": 3, "score": 0.8853049874305725}, {"id": "https://openalex.org/C101721835", "wikidata": "https://www.wikidata.org/wiki/Q813908", "display_name": "Conditional entropy", "level": 3, "score": 0.8247196078300476}, {"id": "https://openalex.org/C35639132", "wikidata": "https://www.wikidata.org/wiki/Q7452468", "display_name": "Sequence labeling", "level": 3, "score": 0.7765474915504456}, {"id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 0.656731128692627}, {"id": "https://openalex.org/C154945302", "wikidata": "https://www.wikidata.org/wiki/Q11660", "display_name": "Artificial intelligence", "level": 1, "score": 0.6271525621414185}, {"id": "https://openalex.org/C106301342", "wikidata": "https://www.wikidata.org/wiki/Q4117933", "display_name": "Entropy (arrow of time)", "level": 2, "score": 0.5572037100791931}, {"id": "https://openalex.org/C119857082", "wikidata": "https://www.wikidata.org/wiki/Q2539", "display_name": "Machine learning", "level": 1, "score": 0.5383710861206055}, {"id": "https://openalex.org/C2776135515", "wikidata": "https://www.wikidata.org/wiki/Q17143721", "display_name": "Regularization (linguistics)", "level": 2, "score": 0.5360749959945679}, {"id": "https://openalex.org/C22367795", "wikidata": "https://www.wikidata.org/wiki/Q7625208", "display_name": "Structured prediction", "level": 2, "score": 0.4671812653541565}, {"id": "https://openalex.org/C89600930", "wikidata": "https://www.wikidata.org/wiki/Q1423946", "display_name": "Segmentation", "level": 2, "score": 0.44676434993743896}, {"id": "https://openalex.org/C153180895", "wikidata": "https://www.wikidata.org/wiki/Q7148389", "display_name": "Pattern recognition (psychology)", "level": 2, "score": 0.44383111596107483}, {"id": "https://openalex.org/C167981619", "wikidata": "https://www.wikidata.org/wiki/Q1685498", "display_name": "Cross entropy", "level": 3, "score": 0.443760484457016}, {"id": "https://openalex.org/C9679016", "wikidata": "https://www.wikidata.org/wiki/Q1417473", "display_name": "Principle of maximum entropy", "level": 2, "score": 0.37270182371139526}, {"id": "https://openalex.org/C162324750", "wikidata": "https://www.wikidata.org/wiki/Q8134", "display_name": "Economics", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C187736073", "wikidata": "https://www.wikidata.org/wiki/Q2920921", "display_name": "Management", "level": 1, "score": 0.0}, {"id": "https://openalex.org/C121332964", "wikidata": "https://www.wikidata.org/wiki/Q413", "display_name": "Physics", "level": 0, "score": 0.0}, {"id": "https://openalex.org/C2780451532", "wikidata": "https://www.wikidata.org/wiki/Q759676", "display_name": "Task (project management)", "level": 2, "score": 0.0}, {"id": "https://openalex.org/C62520636", "wikidata": "https://www.wikidata.org/wiki/Q944", "display_name": "Quantum mechanics", "level": 1, "score": 0.0}], "mesh": [], "locations_count": 7, "locations": [{"id": "doi:10.3115/1220175.1220202", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1220175.1220202", "pdf_url": "https://dl.acm.org/doi/pdf/10.3115/1220175.1220202", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the ACL - ACL '06", "raw_type": "proceedings-article"}, {"id": "pmh:oai:corescholar.libraries.wright.edu:knoesis-1099", "is_oa": false, "landing_page_url": "https://corescholar.libraries.wright.edu/knoesis/100", "pdf_url": null, "source": {"id": "https://openalex.org/S2737205702", "display_name": "Journal of Bioresource Management", "issn_l": "2309-3854", "issn": ["2309-3854"], "is_oa": false, "is_in_doaj": true, "is_core": false, "host_organization": "https://openalex.org/P4310316536", "host_organization_name": "Bioresource Research Center (BRC), Islamabad", "host_organization_lineage": ["https://openalex.org/P4310316536"], "host_organization_lineage_names": ["Bioresource Research Center (BRC), Islamabad"], "type": "journal"}, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "Kno.e.sis Publications", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.143.8340", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.143.8340", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://acl.ldc.upenn.edu/P/P06/P06-1027.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.333.7178", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.333.7178", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://webdocs.cs.ualberta.ca/~fjiao/acl2006.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.69.4455", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.69.4455", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cs.ualberta.ca/~dale/papers/acl06.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.83.3114", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.83.3114", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.metabolomics.ca/News/publications/Jiao_et_al.pdf", "raw_type": "text"}, {"id": "pmh:oai:CiteSeerX.psu:10.1.1.87.1928", "is_oa": false, "landing_page_url": "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.87.1928", "pdf_url": null, "source": null, "license": null, "license_id": null, "version": "submittedVersion", "is_accepted": false, "is_published": false, "raw_source_name": "http://www.cs.ualberta.ca/~swang/acl2006.pdf", "raw_type": "text"}], "best_oa_location": {"id": "doi:10.3115/1220175.1220202", "is_oa": true, "landing_page_url": "https://doi.org/10.3115/1220175.1220202", "pdf_url": "https://dl.acm.org/doi/pdf/10.3115/1220175.1220202", "source": null, "license": null, "license_id": null, "version": "publishedVersion", "is_accepted": true, "is_published": true, "raw_source_name": "Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the ACL - ACL '06", "raw_type": "proceedings-article"}, "sustainable_development_goals": [{"display_name": "Quality Education", "score": 0.47999998927116394, "id": "https://metadata.un.org/sdg/4"}], "awards": [], "funders": [{"id": "https://openalex.org/F4320310787", "display_name": "Genome Canada", "ror": "https://ror.org/029s29983"}, {"id": "https://openalex.org/F4320326646", "display_name": "Genome Alberta", "ror": null}], "has_content": {"grobid_xml": true, "pdf": true}, "content_urls": {"pdf": "https://content.openalex.org/works/W2150969560.pdf", "grobid_xml": "https://content.openalex.org/works/W2150969560.grobid-xml"}, "referenced_works_count": 26, "referenced_works": ["https://openalex.org/W141372029", "https://openalex.org/W1991448974", "https://openalex.org/W2044442377", "https://openalex.org/W2048679005", "https://openalex.org/W2059279601", "https://openalex.org/W2095758845", "https://openalex.org/W2097089247", "https://openalex.org/W2099111195", "https://openalex.org/W2101210369", "https://openalex.org/W2109189215", "https://openalex.org/W2131775048", "https://openalex.org/W2139823104", "https://openalex.org/W2145494108", "https://openalex.org/W2147880316", "https://openalex.org/W2151296343", "https://openalex.org/W2152005244", "https://openalex.org/W2154455818", "https://openalex.org/W2165922980", "https://openalex.org/W2293363371", "https://openalex.org/W2296319761", "https://openalex.org/W2501155501", "https://openalex.org/W3016210511", "https://openalex.org/W3017143921", "https://openalex.org/W4293775970", "https://openalex.org/W6648121996", "https://openalex.org/W6682494755"], "related_works": ["https://openalex.org/W3015678144", "https://openalex.org/W2962906565", "https://openalex.org/W2798423868", "https://openalex.org/W142195158", "https://openalex.org/W2011251309", "https://openalex.org/W2385117199", "https://openalex.org/W2137657024", "https://openalex.org/W2150969560", "https://openalex.org/W2156161585", "https://openalex.org/W197206975"], "abstract_inverted_index": {"We": [0, 86], "present": [1], "a": [2, 23, 48], "new": [3, 89], "semi-supervised": [4], "training": [5, 29, 49, 62, 90], "procedure": [6], "for": [7], "conditional": [8, 54, 58], "random": [9], "fields": [10], "(CRFs)": [11], "that": [12, 51, 106], "can": [13, 69], "be": [14, 71], "used": [15, 72], "to": [16, 42, 73, 92], "train": [17], "sequence": [18], "segmentors": [19], "and": [20, 27, 98, 104], "labelers": [21], "from": [22, 80], "combination": [24], "of": [25, 95, 113], "labeled": [26, 57], "unlabeled": [28, 53, 108], "data.": [30], "Our": [31], "approach": [32], "is": [33, 64], "based": [34], "on": [35], "extending": [36], "the": [37, 43, 61, 93, 111, 114], "minimum": [38], "entropy": [39, 55], "regularization": [40], "framework": [41], "structured": [44], "prediction": [45], "case,": [46], "yielding": [47], "objective": [50, 63], "combines": [52], "with": [56], "likelihood.": [59], "Although": [60], "no": [65], "longer": [66], "concave,": [67], "it": [68], "still": [70], "improve": [74], "an": [75], "initial": [76], "model": [77], "(e.g.": [78], "obtained": [79], "supervised": [81, 115], "training)": [82], "by": [83], "iterative": [84], "ascent.": [85], "apply": [87], "our": [88], "algorithm": [91], "problem": [94], "identifying": [96], "gene": [97], "protein": [99], "mentions": [100], "in": [101, 117], "biological": [102], "texts,": [103], "show": [105], "incorporating": [107], "data": [109], "improves": [110], "performance": [112], "CRF": [116], "this": [118], "case.": [119]}, "counts_by_year": [{"year": 2025, "cited_by_count": 1}, {"year": 2022, "cited_by_count": 1}, {"year": 2021, "cited_by_count": 1}, {"year": 2020, "cited_by_count": 4}, {"year": 2019, "cited_by_count": 7}, {"year": 2018, "cited_by_count": 3}, {"year": 2017, "cited_by_count": 3}, {"year": 2016, "cited_by_count": 7}, {"year": 2015, "cited_by_count": 3}, {"year": 2014, "cited_by_count": 12}, {"year": 2013, "cited_by_count": 10}, {"year": 2012, "cited_by_count": 19}], "updated_date": "2026-07-29T14:22:42.915294", "created_date": "2025-10-10T00:00:00"}], "group_by": []}