{"id":"https://openalex.org/W142561815","doi":null,"title":"Multiple Alignment of Citation Sentences with Conditional Random Fields and Posterior Decoding","display_name":"Multiple Alignment of Citation Sentences with Conditional Random Fields and Posterior Decoding","publication_year":2007,"publication_date":"2007-06-01","ids":{"openalex":"https://openalex.org/W142561815","mag":"142561815"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.132.7908","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.132.7908","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://biotext.berkeley.edu/papers/mca_emnlp07.pdf","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Ariel Schwartz","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ariel Schwartz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061024321","display_name":"Anna Divoli","orcid":"https://orcid.org/0000-0003-2324-3542","observed_orcids":["https://orcid.org/0000-0003-2324-3542"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anna Divoli","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-2324-3542","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5019933387","display_name":"Marti A. Hearst","orcid":"https://orcid.org/0000-0002-4346-1603","observed_orcids":["https://orcid.org/0000-0002-4346-1603"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marti A. Hearst","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-4346-1603","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0741,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.81103401,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"847","last_page":"857"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.7968999743461609,"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":0.7968999743461609,"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":0.16930000483989716,"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":0.006800000090152025,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/multiple-sequence-alignment","display_name":"multiple sequence alignment","score":0.718999981880188},{"id":"https://openalex.org/keywords/word-alignment","display_name":"word alignment","score":0.8669999837875366},{"id":"https://openalex.org/keywords/conditional-random-fields","display_name":"conditional random fields","score":0.9190000295639038},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"semantic similarity","score":0.7879999876022339},{"id":"https://openalex.org/keywords/scientific-publications","display_name":"scientific publications","score":0.7889999747276306},{"id":"https://openalex.org/keywords/named-entity-recognition","display_name":"named entity recognition","score":0.4480000138282776},{"id":"https://openalex.org/keywords/synonym-identification","display_name":"synonym identification","score":0.6320000290870667},{"id":"https://openalex.org/keywords/summarization","display_name":"summarization","score":0.593999981880188}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8174323439598083},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7612935304641724},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.656647264957428},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6311774253845215},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.6207249164581299},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6170608997344971},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.535519003868103},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5290823578834534},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5283872485160828},{"id":"https://openalex.org/C88031987","wikidata":"https://www.wikidata.org/wiki/Q1377767","display_name":"Multiple sequence alignment","level":5,"score":0.5171429514884949},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4618804156780243},{"id":"https://openalex.org/C98893333","wikidata":"https://www.wikidata.org/wiki/Q4339878","display_name":"Ontology alignment","level":4,"score":0.45618975162506104},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.45024797320365906},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4427955746650696},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.36411577463150024},{"id":"https://openalex.org/C45484198","wikidata":"https://www.wikidata.org/wiki/Q827246","display_name":"Sequence alignment","level":4,"score":0.3275647461414337},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22273680567741394},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13277798891067505},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10043644905090332},{"id":"https://openalex.org/C167625842","wikidata":"https://www.wikidata.org/wiki/Q899763","display_name":"Peptide sequence","level":3,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"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/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/C22550185","wikidata":"https://www.wikidata.org/wiki/Q7095047","display_name":"Ontology-based data integration","level":3,"score":0.0},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.132.7908","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.132.7908","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://biotext.berkeley.edu/papers/mca_emnlp07.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.80.6828","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.80.6828","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/D/D07/D07-1089.pdf","raw_type":"text"},{"id":"mag:142561815","doi":null,"is_oa":false,"landing_page_url":"https://biotext.berkeley.edu/papers/mca_emnlp07.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4363608991","display_name":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":false,"raw_source_name":"Empirical Methods in Natural Language Processing","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1261864449","https://openalex.org/W1480741751","https://openalex.org/W1487863191","https://openalex.org/W1521062204","https://openalex.org/W1522389045","https://openalex.org/W1647729745","https://openalex.org/W1866859902","https://openalex.org/W2009570821","https://openalex.org/W2019443264","https://openalex.org/W2022878576","https://openalex.org/W2043650643","https://openalex.org/W2046463720","https://openalex.org/W2069656088","https://openalex.org/W2073234837","https://openalex.org/W2078762661","https://openalex.org/W2087551996","https://openalex.org/W2090694501","https://openalex.org/W2122244345","https://openalex.org/W2124810114","https://openalex.org/W2127686544","https://openalex.org/W2141532438","https://openalex.org/W2147880316","https://openalex.org/W2152183901","https://openalex.org/W2156985047","https://openalex.org/W2168190036","https://openalex.org/W2169724380","https://openalex.org/W2243001382","https://openalex.org/W2608053747","https://openalex.org/W3214380909"],"related_works":["https://openalex.org/W2481193144","https://openalex.org/W2727809068","https://openalex.org/W2538876338","https://openalex.org/W4206894035","https://openalex.org/W7054548519","https://openalex.org/W2616289657","https://openalex.org/W3213981305","https://openalex.org/W3173401931","https://openalex.org/W7039174465","https://openalex.org/W1952210680"],"abstract_inverted_index":{"In":[0,23,78],"scientific":[1],"literature,":[2],"sentences":[3,44],"that":[4,129],"cite":[5],"related":[6,68],"work":[7],"can":[8],"be":[9],"a":[10,107,132],"valuable":[11],"resource":[12],"for":[13],"applications":[14],"such":[15],"as":[16],"summarization,":[17],"synonym":[18],"identification,":[19],"and":[20,64,92,106],"entity":[21],"extraction.":[22],"order":[24],"to":[25,46,54,69],"determine":[26],"which":[27],"equivalent":[28],"entities":[29],"are":[30],"discussed":[31],"in":[32,61,74],"the":[33,40,55,62,70,83,94,122],"various":[34],"citation":[35,87],"sentences,":[36],"we":[37,81],"propose":[38],"aligning":[39],"words":[41],"within":[42],"these":[43],"according":[45],"semantic":[47],"similarity.":[48],"This":[49],"problem":[50,56,73,84],"is":[51,65],"partly":[52],"analogous":[53],"of":[57,85,101,115],"multiple":[58,86,111],"sequence":[59,112],"alignment":[60,72,89,99,113],"biosciences,":[63],"also":[66],"closely":[67],"word":[71,98],"statistical":[75],"machine":[76],"translation.":[77],"this":[79],"paper":[80],"address":[82],"concept":[88],"by":[90],"combining":[91],"modifying":[93],"CRF":[95],"based":[96,110],"pairwise":[97],"system":[100],"Blunsom":[102],"&":[103,117],"Cohn":[104],"(2006)":[105],"posterior":[108],"decoding":[109],"algorithm":[114,123],"Schwartz":[116],"Pachter":[118],"(2007).":[119],"We":[120],"evaluate":[121],"on":[124,131],"hand-labeled":[125],"data,":[126],"achieving":[127],"results":[128],"improve":[130],"baseline.":[133],"1":[134]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":3}],"updated_date":"2026-10-31T12:09:11.096373","created_date":"2016-06-24T00:00:00"}