{"id":"https://openalex.org/W2164755781","doi":"https://doi.org/10.3115/v1/d14-1085","title":"Unsupervised Sentence Enhancement for Automatic Summarization","display_name":"Unsupervised Sentence Enhancement for Automatic Summarization","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2164755781","doi":"https://doi.org/10.3115/v1/d14-1085","mag":"2164755781"},"language":"en","primary_location":{"id":"doi:10.3115/v1/d14-1085","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/d14-1085","pdf_url":"https://aclanthology.org/D14-1085.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 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/D14-1085.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050801868","display_name":"Jackie Chi Kit Cheung","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":false,"raw_author_name":"Jackie Chi Kit Cheung","raw_affiliation_strings":["University of Toronto"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Toronto","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052428595","display_name":"Gerald Penn","orcid":"https://orcid.org/0000-0003-3553-8305"},"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":false,"raw_author_name":"Gerald Penn","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":[],"corresponding_institution_ids":["https://openalex.org/I185261750"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"775","last_page":"786"},"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":0.9998999834060669,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9943000078201294,"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/grammaticality","display_name":"Grammaticality","score":0.8939669132232666},{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.878440797328949},{"id":"https://openalex.org/keywords/coreference","display_name":"Coreference","score":0.8369544744491577},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8245576620101929},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.8081611394882202},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7250242829322815},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6641226410865784},{"id":"https://openalex.org/keywords/source-text","display_name":"Source text","score":0.5949482321739197},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.4252021908760071},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4184114336967468},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.4171569347381592},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.1681506335735321},{"id":"https://openalex.org/keywords/grammar","display_name":"Grammar","score":0.11673352122306824},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06411963701248169}],"concepts":[{"id":"https://openalex.org/C2779525943","wikidata":"https://www.wikidata.org/wiki/Q1187300","display_name":"Grammaticality","level":3,"score":0.8939669132232666},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.878440797328949},{"id":"https://openalex.org/C28076734","wikidata":"https://www.wikidata.org/wiki/Q63087","display_name":"Coreference","level":3,"score":0.8369544744491577},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8245576620101929},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.8081611394882202},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7250242829322815},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6641226410865784},{"id":"https://openalex.org/C120012220","wikidata":"https://www.wikidata.org/wiki/Q1754533","display_name":"Source text","level":2,"score":0.5949482321739197},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.4252021908760071},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4184114336967468},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4171569347381592},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.1681506335735321},{"id":"https://openalex.org/C26022165","wikidata":"https://www.wikidata.org/wiki/Q8091","display_name":"Grammar","level":2,"score":0.11673352122306824},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06411963701248169},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3115/v1/d14-1085","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/d14-1085","pdf_url":"https://aclanthology.org/D14-1085.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 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.653.7753","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.653.7753","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/D/D14/D14-1085.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.682.8235","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.682.8235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://emnlp2014.org/papers/pdf/EMNLP2014085.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.3115/v1/d14-1085","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/d14-1085","pdf_url":"https://aclanthology.org/D14-1085.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 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W2164755781.pdf"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1498416817","https://openalex.org/W1513168555","https://openalex.org/W1552023264","https://openalex.org/W1573537589","https://openalex.org/W1662133657","https://openalex.org/W1860244352","https://openalex.org/W2012561700","https://openalex.org/W2036484499","https://openalex.org/W2050215749","https://openalex.org/W2083451366","https://openalex.org/W2085116970","https://openalex.org/W2097120204","https://openalex.org/W2111646879","https://openalex.org/W2115322217","https://openalex.org/W2118119027","https://openalex.org/W2126920742","https://openalex.org/W2139621418","https://openalex.org/W2151552691","https://openalex.org/W2160017075","https://openalex.org/W2160583993","https://openalex.org/W2250405974","https://openalex.org/W2251303282","https://openalex.org/W2293778248","https://openalex.org/W2397230076"],"related_works":["https://openalex.org/W2040148825","https://openalex.org/W2008201918","https://openalex.org/W2904417864","https://openalex.org/W2549543955","https://openalex.org/W2170375985","https://openalex.org/W1967141764","https://openalex.org/W2956328531","https://openalex.org/W4386840120","https://openalex.org/W2024670813","https://openalex.org/W4390945459"],"abstract_inverted_index":{"We":[0,92],"present":[1],"sentence":[2,21,23,41],"enhancement":[3,24,80],"as":[4],"a":[5,59],"novel":[6],"technique":[7],"for":[8],"text-to-text":[9,96],"genera-tion":[10],"in":[11,63,70],"abstractive":[12],"summarization.":[13],"Com-pared":[14],"to":[15,20,99],"extraction":[16],"or":[17],"previous":[18],"approaches":[19],"fusion,":[22],"increases":[25],"the":[26,34,43,76,105],"range":[27],"of":[28,36,65,72,78],"possible":[29],"summary":[30,53,112,119],"sentences":[31,54],"by":[32,108],"allowing":[33],"combination":[35],"dependency":[37],"subtrees":[38],"from":[39,42],"any":[40],"source":[44,106],"text.":[45],"Our":[46],"experiments":[47],"in-dicate":[48],"that":[49,55,75],"our":[50],"approach":[51],"yields":[52],"are":[56],"competitive":[57],"with":[58],"sen-tence":[60,79],"fusion":[61],"baseline":[62],"terms":[64,71],"con-tent":[66],"quality,":[67],"but":[68],"better":[69],"gram-maticality,":[73],"and":[74],"benefit":[77],"relies":[81],"crucially":[82],"on":[83],"an":[84],"event":[85],"coreference":[86],"resolution":[87],"algorithm":[88],"us-ing":[89],"distributional":[90],"semantics.":[91],"also":[93],"consider":[94],"how":[95,110],"generation":[97],"ap-proaches":[98],"summarization":[100],"can":[101],"be":[102],"ex-tended":[103],"beyond":[104],"text":[107],"exam-ining":[109],"human":[111],"writers":[113],"incor-porate":[114],"source-text-external":[115],"elements":[116],"into":[117],"their":[118],"sentences.":[120],"1":[121]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}