{"id":"https://openalex.org/W2132024321","doi":"https://doi.org/10.3115/1118693.1118723","title":"Using the web to overcome data sparseness","display_name":"Using the web to overcome data sparseness","publication_year":2002,"publication_date":"2002-01-01","ids":{"openalex":"https://openalex.org/W2132024321","doi":"https://doi.org/10.3115/1118693.1118723","mag":"2132024321"},"language":"en","primary_location":{"id":"doi:10.3115/1118693.1118723","is_oa":true,"landing_page_url":"https://doi.org/10.3115/1118693.1118723","pdf_url":"https://dl.acm.org/doi/pdf/10.3115/1118693.1118723","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACL-02 conference on Empirical methods in natural language processing  - EMNLP '02","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/10.3115/1118693.1118723","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054936589","display_name":"Frank Keller","orcid":"https://orcid.org/0000-0002-8242-4362"},"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":"Frank Keller","raw_affiliation_strings":["University of Edinburgh, Edinburgh, UK","University of Edinburgh, Edinburgh , UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Edinburgh, Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]},{"raw_affiliation_string":"University of Edinburgh, Edinburgh , UK","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036055337","display_name":"Maria Lapata","orcid":null},"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":"Maria Lapata","raw_affiliation_strings":["University of Edinburgh, Edinburgh, UK","University of Edinburgh, Edinburgh , UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Edinburgh, Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]},{"raw_affiliation_string":"University of Edinburgh, Edinburgh , UK","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090536256","display_name":"Olga Ourioupina","orcid":null},"institutions":[{"id":"https://openalex.org/I91712215","display_name":"Saarland University","ror":"https://ror.org/01jdpyv68","country_code":"DE","type":"education","lineage":["https://openalex.org/I91712215"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Olga Ourioupina","raw_affiliation_strings":["Saarland University, Saarbr\u00fccken, Germany","Saarland Univ., Saarbr\u00fccken, Germany#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Saarland University, Saarbr\u00fccken, Germany","institution_ids":["https://openalex.org/I91712215"]},{"raw_affiliation_string":"Saarland Univ., Saarbr\u00fccken, Germany#TAB#","institution_ids":["https://openalex.org/I91712215"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":97,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":null,"first_page":"230","last_page":"237"},"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":0.9997000098228455,"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/T13083","display_name":"Advanced Text Analysis Techniques","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/bigram","display_name":"Bigram","score":0.9821912050247192},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.796804666519165},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.607844352722168},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5854020714759827},{"id":"https://openalex.org/keywords/verb","display_name":"Verb","score":0.5745407342910767},{"id":"https://openalex.org/keywords/noun","display_name":"Noun","score":0.5467849373817444},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5428563952445984},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.47770264744758606},{"id":"https://openalex.org/keywords/adjective","display_name":"Adjective","score":0.46653372049331665},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.41827359795570374},{"id":"https://openalex.org/keywords/trigram","display_name":"Trigram","score":0.11470583081245422}],"concepts":[{"id":"https://openalex.org/C108757681","wikidata":"https://www.wikidata.org/wiki/Q2773912","display_name":"Bigram","level":3,"score":0.9821912050247192},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.796804666519165},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.607844352722168},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5854020714759827},{"id":"https://openalex.org/C2776397901","wikidata":"https://www.wikidata.org/wiki/Q24905","display_name":"Verb","level":2,"score":0.5745407342910767},{"id":"https://openalex.org/C121934690","wikidata":"https://www.wikidata.org/wiki/Q1084","display_name":"Noun","level":2,"score":0.5467849373817444},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5428563952445984},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.47770264744758606},{"id":"https://openalex.org/C2777683214","wikidata":"https://www.wikidata.org/wiki/Q34698","display_name":"Adjective","level":3,"score":0.46653372049331665},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.41827359795570374},{"id":"https://openalex.org/C137546455","wikidata":"https://www.wikidata.org/wiki/Q3213474","display_name":"Trigram","level":2,"score":0.11470583081245422},{"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}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3115/1118693.1118723","is_oa":true,"landing_page_url":"https://doi.org/10.3115/1118693.1118723","pdf_url":"https://dl.acm.org/doi/pdf/10.3115/1118693.1118723","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACL-02 conference on Empirical methods in natural language processing  - EMNLP '02","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.11.9365","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.11.9365","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/jimmylin/papers/Keller02.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.15.1298","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.1298","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.cornell.edu/Courses/cs775/2002fa/papers/keller-etal-emnlp02.pdf","raw_type":"text"},{"id":"pmh:oai:pure.ed.ac.uk:openaire/c38241b3-2c40-4d09-85ca-f8c4a8f49f66","is_oa":true,"landing_page_url":"https://hdl.handle.net/20.500.11820/c38241b3-2c40-4d09-85ca-f8c4a8f49f66","pdf_url":null,"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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Keller, F, Lapata, M & Ourioupina, O 2002, Using the Web to Overcome Data Sparseness. in EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing. vol. 10, Stroudsburg, PA, pp. 230-237, 7th Conference on Empirical Methods in Natural Language Processing (EMNLP 2002), Philadelphia, PA, United States, 6/07/02. < http://aclweb.org/anthology/W02-1030 >","raw_type":"bookPart"},{"id":"pmh:oai:pure.ed.ac.uk:publications/c38241b3-2c40-4d09-85ca-f8c4a8f49f66","is_oa":false,"landing_page_url":"https://www.research.ed.ac.uk/en/publications/c38241b3-2c40-4d09-85ca-f8c4a8f49f66","pdf_url":null,"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":"doi:10.3115/1118693.1118723","is_oa":true,"landing_page_url":"https://doi.org/10.3115/1118693.1118723","pdf_url":"https://dl.acm.org/doi/pdf/10.3115/1118693.1118723","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACL-02 conference on Empirical methods in natural language processing  - EMNLP '02","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7699999809265137,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2132024321.pdf","grobid_xml":"https://content.openalex.org/works/W2132024321.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W1489384387","https://openalex.org/W1516391399","https://openalex.org/W1540931780","https://openalex.org/W1578564752","https://openalex.org/W1593239840","https://openalex.org/W1991158387","https://openalex.org/W1998641229","https://openalex.org/W2031344788","https://openalex.org/W2035967403","https://openalex.org/W2048021297","https://openalex.org/W2068017609","https://openalex.org/W2073677209","https://openalex.org/W2102381086","https://openalex.org/W2104232304","https://openalex.org/W2115983295","https://openalex.org/W2120084270","https://openalex.org/W2129626314","https://openalex.org/W2132851324","https://openalex.org/W2145080939","https://openalex.org/W2157963512","https://openalex.org/W2161821575","https://openalex.org/W2183330546","https://openalex.org/W2213505007","https://openalex.org/W2949109629","https://openalex.org/W2949791182","https://openalex.org/W3021516576","https://openalex.org/W4285719527","https://openalex.org/W4388152766"],"related_works":["https://openalex.org/W4312381793","https://openalex.org/W2385963184","https://openalex.org/W2350058787","https://openalex.org/W3139255945","https://openalex.org/W2976849154","https://openalex.org/W3112308623","https://openalex.org/W578924573","https://openalex.org/W2902614234","https://openalex.org/W2068167831","https://openalex.org/W4388156376"],"abstract_inverted_index":{"This":[0],"paper":[1],"shows":[2],"that":[3,14,48,69],"the":[4,35],"web":[5,36,49,70],"can":[6,72],"be":[7],"employed":[8],"to":[9],"obtain":[10],"frequencies":[11,50,54,71],"for":[12,25,28],"bigrams":[13,33],"are":[15],"unseen":[16],"in":[17],"a":[18,23,39,57,65],"given":[19],"corpus.":[20,61],"We":[21,42,62],"describe":[22],"method":[24,45],"retrieving":[26],"counts":[27],"adjective-noun,":[29],"noun-noun,":[30],"and":[31,51],"verb-object":[32],"from":[34,56],"by":[37,46],"querying":[38],"search":[40],"engine.":[41],"evaluate":[43],"this":[44],"demonstrating":[47],"correlate":[52],"with":[53],"obtained":[55],"carefully":[58],"edited,":[59],"balanced":[60],"also":[63],"perform":[64],"task-based":[66],"evaluation,":[67],"showing":[68],"reliably":[73],"predict":[74],"human":[75],"plausibility":[76],"judgments.":[77]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}