{"id":"https://openalex.org/W2896159974","doi":"https://doi.org/10.1145/3269206.3269251","title":"Attentive Encoder-based Extractive Text Summarization","display_name":"Attentive Encoder-based Extractive Text Summarization","publication_year":2018,"publication_date":"2018-10-17","ids":{"openalex":"https://openalex.org/W2896159974","doi":"https://doi.org/10.1145/3269206.3269251","mag":"2896159974"},"language":"en","primary_location":{"id":"doi:10.1145/3269206.3269251","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3269206.3269251","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066140774","display_name":"Chong Feng","orcid":"https://orcid.org/0000-0002-1691-1584"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chong Feng","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101854790","display_name":"Fei Cai","orcid":"https://orcid.org/0000-0001-6970-5488"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Cai","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026327666","display_name":"Honghui Chen","orcid":"https://orcid.org/0009-0003-5234-0592"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Honghui Chen","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031439294","display_name":"Maarten de Rijke","orcid":"https://orcid.org/0000-0002-1086-0202"},"institutions":[{"id":"https://openalex.org/I4210135670","display_name":"Amsterdam University of the Arts","ror":"https://ror.org/04dde1554","country_code":"NL","type":"education","lineage":["https://openalex.org/I4210135670"]},{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Maarten de Rijke","raw_affiliation_strings":["University of Amsterdam, Amsterdam, Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Amsterdam, Amsterdam, Netherlands","institution_ids":["https://openalex.org/I4210135670","https://openalex.org/I887064364"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4527,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.67328149,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1499","last_page":"1502"},"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":0.9958999752998352,"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/automatic-summarization","display_name":"Automatic summarization","score":0.9657992720603943},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.8969529271125793},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8331206440925598},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.7042793035507202},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6440572142601013},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5472823977470398},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5402472019195557},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5231986045837402},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5221726894378662},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.46118077635765076},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.44432389736175537},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.34560635685920715},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.31091129779815674},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.058439791202545166}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9657992720603943},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.8969529271125793},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8331206440925598},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.7042793035507202},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6440572142601013},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5472823977470398},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5402472019195557},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5231986045837402},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5221726894378662},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.46118077635765076},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.44432389736175537},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.34560635685920715},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.31091129779815674},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.058439791202545166},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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":3,"locations":[{"id":"doi:10.1145/3269206.3269251","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3269206.3269251","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:dare.uva.nl:openaire_cris_publications/d049ded7-6b23-4c58-a0d8-7e785d6e0983","is_oa":false,"landing_page_url":"https://handle.uba.uva.nl/personal/pure/en/publications/attentive-encoderbased-extractive-text-summarization(d049ded7-6b23-4c58-a0d8-7e785d6e0983).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400088","display_name":"UvA-DARE (University of Amsterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887064364","host_organization_name":"University of Amsterdam","host_organization_lineage":["https://openalex.org/I887064364"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Feng, C, Cai, F, Chen, H & de Rijke, M 2018, Attentive Encoder-based Extractive Text Summarization. in CIKM'18 : proceedings of the 2018 ACM International Conference on Information and Knowledge Management : October 22-26, 2018, Torino, Italy. New York, NY, pp. 1499-1502, 27th ACM International Conference on Information and Knowledge Management, CIKM 2018, Torino, Italy, 22/10/18. https://doi.org/10.1145/3269206.3269251","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:uvapub:oai:dare.uva.nl:publications/d049ded7-6b23-4c58-a0d8-7e785d6e0983","is_oa":false,"landing_page_url":"https://dare.uva.nl/personal/pure/en/publications/attentive-encoderbased-extractive-text-summarization(d049ded7-6b23-4c58-a0d8-7e785d6e0983).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"CIKM'18: proceedings of the 2018 ACM International Conference on Information and Knowledge Management : October 22-26, 2018, Torino, Italy, 1499 - 1502","raw_type":"info:eu-repo/semantics/conferencepaper"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W2150824314","https://openalex.org/W2307381258","https://openalex.org/W2574535369","https://openalex.org/W2597655663","https://openalex.org/W2735674392","https://openalex.org/W2952138241","https://openalex.org/W2962974924","https://openalex.org/W2963929190","https://openalex.org/W2964121744","https://openalex.org/W2964308564"],"related_works":["https://openalex.org/W2366403280","https://openalex.org/W1495108544","https://openalex.org/W2091301346","https://openalex.org/W3148229873","https://openalex.org/W4389760904","https://openalex.org/W2150160875","https://openalex.org/W4242223894","https://openalex.org/W4306886878","https://openalex.org/W2973759123","https://openalex.org/W1517524280"],"abstract_inverted_index":{"In":[0],"previous":[1],"work":[2],"on":[3,21],"text":[4],"summarization,":[5],"encoder-decoder":[6,17],"architectures":[7],"and":[8,45,84,98,116],"attention":[9],"mechanisms":[10],"have":[11],"both":[12,77],"been":[13],"widely":[14],"used.":[15],"Attention-based":[16],"approaches":[18],"typically":[19],"focus":[20],"taking":[22],"the":[23,40,54,78,85,90,106],"sentences":[24,46,88],"preceding":[25],"a":[26,30,43,51,71,82,99,136],"given":[27],"sentence":[28,44],"in":[29,50,53,89],"document":[31,35,52,73,83],"into":[32],"account":[33],"for":[34],"representation,":[36],"failing":[37],"to":[38,64,104,110],"capture":[39],"relationships":[41,86],"between":[42],"that":[47,127],"follow":[48],"it":[49],"encoder.":[55],"We":[56,131],"propose":[57],"an":[58],"attentive":[59,112,118],"encoder-based":[60,113,119],"summarization":[61,114,120],"(AES)":[62],"model":[63],"generate":[65,70],"article":[66],"summaries.":[67],"AES":[68],"can":[69],"rich":[72],"representation":[74],"by":[75],"considering":[76],"global":[79],"information":[80],"of":[81,87],"document.":[91],"A":[92],"unidirectional":[93,111],"recurrent":[94],"neural":[95],"network":[96],"(RNN)":[97],"bidirectional":[100,117],"RNN":[101],"are":[102],"considered":[103],"construct":[105],"encoders,":[107],"giving":[108],"rise":[109],"(Uni-AES)":[115],"(Bi-AES),":[121],"respectively.":[122],"Our":[123],"experimental":[124],"results":[125],"show":[126],"Bi-AES":[128],"outperforms":[129],"Uni-AES.":[130],"obtain":[132],"substantial":[133],"improvements":[134],"over":[135],"relevant":[137],"start-of-the-art":[138],"baseline.":[139]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
