{"id":"https://openalex.org/W2928488760","doi":"https://doi.org/10.1109/bigcomp.2019.8679478","title":"Query-Focused Summarization Enhanced with Sentence Attention Mechanism","display_name":"Query-Focused Summarization Enhanced with Sentence Attention Mechanism","publication_year":2019,"publication_date":"2019-02-01","ids":{"openalex":"https://openalex.org/W2928488760","doi":"https://doi.org/10.1109/bigcomp.2019.8679478","mag":"2928488760"},"language":"en","primary_location":{"id":"doi:10.1109/bigcomp.2019.8679478","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigcomp.2019.8679478","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data and Smart Computing (BigComp)","raw_type":"proceedings-article"},"type":"article","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/A5089778645","display_name":"Tasuku Kimura","orcid":null},"institutions":[{"id":"https://openalex.org/I168356945","display_name":"Kyoto Sangyo University","ror":"https://ror.org/05t70xh16","country_code":"JP","type":"education","lineage":["https://openalex.org/I168356945"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Tasuku Kimura","raw_affiliation_strings":["Division of Frontier Informatics, Kyoto Sangyo University, Kyoto, Japan"],"affiliations":[{"raw_affiliation_string":"Division of Frontier Informatics, Kyoto Sangyo University, Kyoto, Japan","institution_ids":["https://openalex.org/I168356945"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058233979","display_name":"Ryo Tagami","orcid":"https://orcid.org/0000-0002-8109-0962"},"institutions":[{"id":"https://openalex.org/I168356945","display_name":"Kyoto Sangyo University","ror":"https://ror.org/05t70xh16","country_code":"JP","type":"education","lineage":["https://openalex.org/I168356945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryo Tagami","raw_affiliation_strings":["Division of Frontier Informatics, Kyoto Sangyo University, Kyoto, Japan"],"affiliations":[{"raw_affiliation_string":"Division of Frontier Informatics, Kyoto Sangyo University, Kyoto, Japan","institution_ids":["https://openalex.org/I168356945"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011329519","display_name":"Hisashi Miyamori","orcid":"https://orcid.org/0000-0003-3833-9512"},"institutions":[{"id":"https://openalex.org/I168356945","display_name":"Kyoto Sangyo University","ror":"https://ror.org/05t70xh16","country_code":"JP","type":"education","lineage":["https://openalex.org/I168356945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hisashi Miyamori","raw_affiliation_strings":["Division of Frontier Informatics, Kyoto Sangyo University, Kyoto, Japan"],"affiliations":[{"raw_affiliation_string":"Division of Frontier Informatics, Kyoto Sangyo University, Kyoto, Japan","institution_ids":["https://openalex.org/I168356945"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5089778645"],"corresponding_institution_ids":["https://openalex.org/I168356945"],"apc_list":null,"apc_paid":null,"fwci":0.14,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.54006467,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"28","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10181","display_name":"Natural Language Processing Techniques","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/T13083","display_name":"Advanced Text Analysis Techniques","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/automatic-summarization","display_name":"Automatic summarization","score":0.8709696531295776},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8192776441574097},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.5738011002540588},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.4926465153694153},{"id":"https://openalex.org/keywords/multi-document-summarization","display_name":"Multi-document summarization","score":0.42916393280029297},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.42624369263648987},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3550654947757721},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.34868282079696655},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.04368898272514343}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8709696531295776},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8192776441574097},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.5738011002540588},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.4926465153694153},{"id":"https://openalex.org/C134714966","wikidata":"https://www.wikidata.org/wiki/Q6934448","display_name":"Multi-document summarization","level":3,"score":0.42916393280029297},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.42624369263648987},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3550654947757721},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.34868282079696655},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.04368898272514343},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigcomp.2019.8679478","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigcomp.2019.8679478","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data and Smart Computing (BigComp)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1486649854","https://openalex.org/W1522301498","https://openalex.org/W1974339500","https://openalex.org/W2064675550","https://openalex.org/W2123442489","https://openalex.org/W2130942839","https://openalex.org/W2131744502","https://openalex.org/W2133564696","https://openalex.org/W2153579005","https://openalex.org/W2154652894","https://openalex.org/W2157331557","https://openalex.org/W2166347079","https://openalex.org/W2561658355","https://openalex.org/W2747263644","https://openalex.org/W2761988601","https://openalex.org/W2766273648","https://openalex.org/W2807008868","https://openalex.org/W2962965405","https://openalex.org/W2962966181","https://openalex.org/W2963443217","https://openalex.org/W2963506925","https://openalex.org/W2963918774","https://openalex.org/W2964121744","https://openalex.org/W2964308564","https://openalex.org/W4294170691","https://openalex.org/W6629028937","https://openalex.org/W6631190155","https://openalex.org/W6679436768","https://openalex.org/W6679775712","https://openalex.org/W6682631176","https://openalex.org/W6682691769","https://openalex.org/W6702212959","https://openalex.org/W6745115194","https://openalex.org/W6752183284"],"related_works":["https://openalex.org/W3164984162","https://openalex.org/W2104677027","https://openalex.org/W2902627734","https://openalex.org/W2112885393","https://openalex.org/W2173208124","https://openalex.org/W2568827738","https://openalex.org/W1990695371","https://openalex.org/W2365100044","https://openalex.org/W2099859325","https://openalex.org/W2474342320"],"abstract_inverted_index":{"In":[0,20,59,167,229],"today's":[1],"society":[2],"where":[3],"the":[4,11,24,31,40,50,56,60,66,90,94,108,113,123,127,138,147,150,153,161,164,187,192,201,209,216,223,230,234,239,246,253,256,264],"enormous":[5],"amount":[6],"of":[7,115,140,149,152,163,191,204,219,226,241,263],"documents":[8],"are":[9,99],"overflowing,":[10],"demand":[12],"for":[13],"automatic":[14,61],"text":[15,33],"summarization":[16,52,62,128,235,249],"has":[17],"been":[18],"increasing.":[19],"particular,":[21],"when":[22],"considering":[23,200],"practical":[25],"use,":[26],"it":[27,130],"is":[28,110,131],"expected":[29],"that":[30,53,107,137,158],"query-oriented":[32],"summarization,":[34],"which":[35,74,82,237],"generates":[36],"summaries":[37,199],"focusing":[38],"on":[39,65,85,255],"given":[41],"specific":[42,86],"queries,":[43],"will":[44],"be":[45,134],"more":[46],"important":[47],"rather":[48],"than":[49,118],"generic":[51],"simply":[54],"summarizes":[55],"entire":[57],"document.":[58,194],"methods":[63],"based":[64],"deep":[67],"neural":[68],"model,":[69,250],"Long-Short":[70],"Term":[71],"Memory":[72],"(LSTM)":[73],"enables":[75],"longterm":[76],"information":[77],"storage,":[78],"and":[79,208,222,251],"attention":[80,217,224],"mechanism":[81,218,225,240],"allows":[83],"emphasis":[84],"time":[87],"steps":[88],"from":[89],"vectors":[91],"encoded":[92],"by":[93,178,213,259],"Recurrent":[95],"Neural":[96],"Network":[97],"(RNN),":[98],"essential.":[100],"However,":[101],"Koehn":[102],"et":[103],"al.":[104],"[1]":[105],"report":[106],"accuracy":[109],"degraded":[111],"in":[112,126,184],"encoding":[114,139],"texts":[116],"longer":[117],"60":[119],"tokens":[120],"entered":[121],"into":[122],"LSTM.":[124],"Even":[125],"task,":[129],"considered":[132],"to":[133,174,186,197,245],"a":[135,141,156,172,176,180,205],"problem":[136],"long":[142],"sentence":[143,181,206,227,242,265],"fails":[144],"or":[145,261],"causes":[146],"disappearance":[148],"relation":[151],"sentences,":[154,212],"as":[155],"factor":[157],"greatly":[159],"deteriorates":[160],"quality":[162],"summary":[165,177,257],"result.":[166],"this":[168],"paper,":[169],"we":[170,232],"propose":[171],"method":[173],"generate":[175,198],"introducing":[179],"unit":[182,189,207,221,243],"vector":[183,190,244],"addition":[185],"word":[188,220],"original":[193],"We":[195],"aim":[196],"importance":[202],"degree":[203],"relations":[210],"between":[211],"learning":[214],"both":[215],"unit.":[228],"experiment,":[231],"examine":[233],"model":[236],"added":[238],"latest":[247],"query-focused":[248],"clarify":[252],"influence":[254],"generated":[258],"presence":[260],"absence":[262],"vector.":[266]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}