{"id":"https://openalex.org/W2963711448","doi":"https://doi.org/10.18653/v1/d17-1167","title":"A Question Answering Approach for Emotion Cause Extraction","display_name":"A Question Answering Approach for Emotion Cause Extraction","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2963711448","doi":"https://doi.org/10.18653/v1/d17-1167","mag":"2963711448"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d17-1167","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1167","pdf_url":"https://www.aclweb.org/anthology/D17-1167.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 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D17-1167.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062168574","display_name":"Lin Gui","orcid":"https://orcid.org/0000-0002-8054-9524"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]},{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lin Gui","raw_affiliation_strings":["College of Mathematics and Computer Science, Fuzhou University, China","Shenzhen Graduate School, Harbin Institute of Technology, China"],"affiliations":[{"raw_affiliation_string":"College of Mathematics and Computer Science, Fuzhou University, China","institution_ids":["https://openalex.org/I80947539"]},{"raw_affiliation_string":"Shenzhen Graduate School, Harbin Institute of Technology, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054112657","display_name":"Jiannan Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiannan Hu","raw_affiliation_strings":["Shenzhen Graduate School, Harbin Institute of Technology, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Graduate School, Harbin Institute of Technology, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015709853","display_name":"Yulan He","orcid":"https://orcid.org/0000-0003-3948-5845"},"institutions":[{"id":"https://openalex.org/I169199633","display_name":"Aston University","ror":"https://ror.org/05j0ve876","country_code":"GB","type":"education","lineage":["https://openalex.org/I169199633"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yulan He","raw_affiliation_strings":["School of Engineering and Applied Science, Aston University, United Kingdom"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Applied Science, Aston University, United Kingdom","institution_ids":["https://openalex.org/I169199633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026719663","display_name":"Ruifeng Xu","orcid":"https://orcid.org/0000-0002-4009-5679"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruifeng Xu","raw_affiliation_strings":["Guangdong Provincial Engineering Technology Research Center for Data Science, China","Shenzhen Graduate School, Harbin Institute of Technology, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Engineering Technology Research Center for Data Science, China","institution_ids":[]},{"raw_affiliation_string":"Shenzhen Graduate School, Harbin Institute of Technology, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016391596","display_name":"Qin Lu","orcid":"https://orcid.org/0000-0002-9092-2476"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Lu Qin","raw_affiliation_strings":["Department of Computing, the Hong Kong Polytechnic University, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computing, the Hong Kong Polytechnic University, Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101733762","display_name":"Jiachen Du","orcid":"https://orcid.org/0000-0002-6284-7691"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiachen Du","raw_affiliation_strings":["Shenzhen Graduate School, Harbin Institute of Technology, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Graduate School, Harbin Institute of Technology, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5062168574"],"corresponding_institution_ids":["https://openalex.org/I204983213","https://openalex.org/I80947539"],"apc_list":null,"apc_paid":null,"fwci":17.2533,"has_fulltext":true,"cited_by_count":187,"citation_normalized_percentile":{"value":0.99303092,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1593","last_page":"1602"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","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/T10664","display_name":"Sentiment Analysis and Opinion Mining","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":0.9991000294685364,"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":0.9990000128746033,"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/computer-science","display_name":"Computer science","score":0.8424060344696045},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.7204686999320984},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6377202272415161},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6337025165557861},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6334627270698547},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6112328767776489},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5696789622306824},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5131962895393372},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4533863961696625},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.44291767477989197},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.43218156695365906},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.12182053923606873}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8424060344696045},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.7204686999320984},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6377202272415161},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6337025165557861},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6334627270698547},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6112328767776489},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5696789622306824},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5131962895393372},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4533863961696625},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.44291767477989197},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.43218156695365906},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.12182053923606873},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"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/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d17-1167","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1167","pdf_url":"https://www.aclweb.org/anthology/D17-1167.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 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d17-1167","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1167","pdf_url":"https://www.aclweb.org/anthology/D17-1167.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 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8600000143051147,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G1291539648","display_name":null,"funder_award_id":"61370165","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2182312180","display_name":null,"funder_award_id":"61528302","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3110231696","display_name":null,"funder_award_id":"U1636103","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3881918265","display_name":null,"funder_award_id":"2015AA015405","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4165806713","display_name":null,"funder_award_id":"61632011","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4243412236","display_name":null,"funder_award_id":"863 Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335773","display_name":"National High-tech Research and Development Program","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963711448.pdf","grobid_xml":"https://content.openalex.org/works/W2963711448.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W25301398","https://openalex.org/W39229845","https://openalex.org/W101809282","https://openalex.org/W152725222","https://openalex.org/W1564070220","https://openalex.org/W1793121960","https://openalex.org/W1832693441","https://openalex.org/W1843891098","https://openalex.org/W1886441443","https://openalex.org/W1902237438","https://openalex.org/W1989145535","https://openalex.org/W1989736506","https://openalex.org/W1992605069","https://openalex.org/W2020111801","https://openalex.org/W2040467972","https://openalex.org/W2093862925","https://openalex.org/W2110432162","https://openalex.org/W2133675239","https://openalex.org/W2136201510","https://openalex.org/W2143219999","https://openalex.org/W2153579005","https://openalex.org/W2161624371","https://openalex.org/W2171578722","https://openalex.org/W2182096631","https://openalex.org/W2229007138","https://openalex.org/W2250246523","https://openalex.org/W2250331987","https://openalex.org/W2250511935","https://openalex.org/W2250666945","https://openalex.org/W2251878733","https://openalex.org/W2252266014","https://openalex.org/W2294062064","https://openalex.org/W2319613444","https://openalex.org/W2379435734","https://openalex.org/W2562539671","https://openalex.org/W2565649476","https://openalex.org/W2951008357","https://openalex.org/W2962750587","https://openalex.org/W2962965405","https://openalex.org/W2963168371","https://openalex.org/W3088107006","https://openalex.org/W3152231500","https://openalex.org/W4231458041","https://openalex.org/W4254003308","https://openalex.org/W4294170691","https://openalex.org/W4301930167"],"related_works":["https://openalex.org/W2384605597","https://openalex.org/W2387743295","https://openalex.org/W3082787378","https://openalex.org/W2136007095","https://openalex.org/W2366230879","https://openalex.org/W3208425359","https://openalex.org/W2349927912","https://openalex.org/W4288102755","https://openalex.org/W3159777597","https://openalex.org/W2755541034"],"abstract_inverted_index":{"Emotion":[0],"cause":[1,47,106],"extraction":[2],"aims":[3],"to":[4,23,66,74],"identify":[5],"the":[6,98],"reasons":[7],"behind":[8],"a":[9,17,41,50,63,102,109],"certain":[10],"emotion":[11,24,46,105],"expressed":[12],"in":[13,30,54,70,118],"text.":[14],"It":[15],"is":[16],"much":[18],"more":[19],"difficult":[20],"task":[21,53],"compared":[22],"classification.":[25],"Inspired":[26,56],"by":[27,57,114],"recent":[28],"advances":[29],"using":[31],"deep":[32],"memory":[33,72],"networks":[34],"for":[35],"question":[36],"answering":[37],"(QA),":[38],"we":[39,61],"propose":[40,62],"new":[42,64],"approach":[43,80],"which":[44],"considers":[45],"identification":[48],"as":[49],"reading":[51],"comprehension":[52],"QA.":[55],"convolutional":[58],"neural":[59],"networks,":[60],"mechanism":[65],"store":[67],"relevant":[68],"context":[69,76],"different":[71],"slots":[73],"model":[75],"information.":[77],"Our":[78],"proposed":[79],"can":[81],"extract":[82],"both":[83],"word":[84],"level":[85],"sequence":[86],"features":[87],"and":[88],"lexical":[89],"features.":[90],"Performance":[91],"evaluation":[92],"shows":[93],"that":[94],"our":[95],"method":[96],"achieves":[97],"state-of-the-art":[99],"performance":[100],"on":[101],"recently":[103],"released":[104],"dataset,":[107],"outperforming":[108],"number":[110],"of":[111],"competitive":[112],"baselines":[113],"at":[115],"least":[116],"3.01%":[117],"F-measure.":[119]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":27},{"year":2022,"cited_by_count":25},{"year":2021,"cited_by_count":32},{"year":2020,"cited_by_count":56},{"year":2019,"cited_by_count":17},{"year":2018,"cited_by_count":10}],"updated_date":"2026-04-23T09:07:50.710637","created_date":"2025-10-10T00:00:00"}