{"id":"https://openalex.org/W3096230989","doi":"https://doi.org/10.1109/taffc.2020.3034215","title":"Multi-Label Emotion Detection via Emotion-Specified Feature Extraction and Emotion Correlation Learning","display_name":"Multi-Label Emotion Detection via Emotion-Specified Feature Extraction and Emotion Correlation Learning","publication_year":2020,"publication_date":"2020-10-27","ids":{"openalex":"https://openalex.org/W3096230989","doi":"https://doi.org/10.1109/taffc.2020.3034215","mag":"3096230989"},"language":"en","primary_location":{"id":"doi:10.1109/taffc.2020.3034215","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2020.3034215","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://tokushima-u.repo.nii.ac.jp/records/2008322","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005007844","display_name":"Jiawen Deng","orcid":"https://orcid.org/0000-0003-0602-8250"},"institutions":[{"id":"https://openalex.org/I922474255","display_name":"Tokushima University","ror":"https://ror.org/044vy1d05","country_code":"JP","type":"education","lineage":["https://openalex.org/I922474255"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jiawen Deng","raw_affiliation_strings":["Graduate School of Advanced Technology and Science, Tokushima University, Tokushima, Japan"],"raw_orcid":"https://orcid.org/0000-0003-0602-8250","affiliations":[{"raw_affiliation_string":"Graduate School of Advanced Technology and Science, Tokushima University, Tokushima, Japan","institution_ids":["https://openalex.org/I922474255"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071943346","display_name":"Fuji Ren","orcid":"https://orcid.org/0000-0003-4860-9184"},"institutions":[{"id":"https://openalex.org/I922474255","display_name":"Tokushima University","ror":"https://ror.org/044vy1d05","country_code":"JP","type":"education","lineage":["https://openalex.org/I922474255"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Fuji Ren","raw_affiliation_strings":["Graduate School of Advanced Technology and Science, Tokushima University, Tokushima, Japan"],"raw_orcid":"https://orcid.org/0000-0003-4860-9184","affiliations":[{"raw_affiliation_string":"Graduate School of Advanced Technology and Science, Tokushima University, Tokushima, Japan","institution_ids":["https://openalex.org/I922474255"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I922474255"],"apc_list":{"value":2045,"currency":"USD","value_usd":2045},"apc_paid":null,"fwci":4.4031,"has_fulltext":false,"cited_by_count":91,"citation_normalized_percentile":{"value":0.95331352,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"14","issue":"1","first_page":"475","last_page":"486"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998000264167786,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","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/T11550","display_name":"Text and Document Classification Technologies","score":0.9991999864578247,"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":0.9951000213623047,"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/correlation","display_name":"Correlation","score":0.6995744109153748},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6204608082771301},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5661941766738892},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5619802474975586},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5421333312988281},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.5207964777946472},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5017313957214355},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4881304204463959},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.4827575087547302},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.43735456466674805},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4177302420139313},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.4124358594417572},{"id":"https://openalex.org/keywords/emotion-perception","display_name":"Emotion perception","score":0.4113022983074188},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1830907166004181},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.17589294910430908},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07800579071044922}],"concepts":[{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.6995744109153748},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6204608082771301},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5661941766738892},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5619802474975586},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5421333312988281},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.5207964777946472},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5017313957214355},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4881304204463959},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.4827575087547302},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.43735456466674805},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4177302420139313},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.4124358594417572},{"id":"https://openalex.org/C2776141551","wikidata":"https://www.wikidata.org/wiki/Q16000087","display_name":"Emotion perception","level":3,"score":0.4113022983074188},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1830907166004181},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.17589294910430908},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07800579071044922},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"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":2,"locations":[{"id":"doi:10.1109/taffc.2020.3034215","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2020.3034215","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"},{"id":"pmh:oai:irdb.nii.ac.jp:00906:0006780250","is_oa":true,"landing_page_url":"https://tokushima-u.repo.nii.ac.jp/records/2008322","pdf_url":null,"source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal article"}],"best_oa_location":{"id":"pmh:oai:irdb.nii.ac.jp:00906:0006780250","is_oa":true,"landing_page_url":"https://tokushima-u.repo.nii.ac.jp/records/2008322","pdf_url":null,"source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W24085112","https://openalex.org/W46659105","https://openalex.org/W1832693441","https://openalex.org/W1924770834","https://openalex.org/W1966797434","https://openalex.org/W1986159170","https://openalex.org/W1999954155","https://openalex.org/W2040467972","https://openalex.org/W2094244309","https://openalex.org/W2116261113","https://openalex.org/W2119466907","https://openalex.org/W2150193144","https://openalex.org/W2154970010","https://openalex.org/W2166950155","https://openalex.org/W2288282342","https://openalex.org/W2400397113","https://openalex.org/W2404480901","https://openalex.org/W2470673105","https://openalex.org/W2563741043","https://openalex.org/W2582715667","https://openalex.org/W2604675517","https://openalex.org/W2740550900","https://openalex.org/W2740721704","https://openalex.org/W2783365884","https://openalex.org/W2786485441","https://openalex.org/W2791506524","https://openalex.org/W2800534405","https://openalex.org/W2806227953","https://openalex.org/W2806731175","https://openalex.org/W2884287800","https://openalex.org/W2886936548","https://openalex.org/W2887558567","https://openalex.org/W2889190301","https://openalex.org/W2889271120","https://openalex.org/W2889855823","https://openalex.org/W2891424355","https://openalex.org/W2891537168","https://openalex.org/W2893202042","https://openalex.org/W2896457183","https://openalex.org/W2899087822","https://openalex.org/W2904300840","https://openalex.org/W2908347420","https://openalex.org/W2913692705","https://openalex.org/W2933162517","https://openalex.org/W2943846412","https://openalex.org/W2949998441","https://openalex.org/W2950318504","https://openalex.org/W2951278869","https://openalex.org/W2963168371","https://openalex.org/W2963248507","https://openalex.org/W2963270153","https://openalex.org/W2963351448","https://openalex.org/W2963391817","https://openalex.org/W2963784080","https://openalex.org/W2964225211","https://openalex.org/W2964309167","https://openalex.org/W2993915582","https://openalex.org/W4254254617","https://openalex.org/W6601005377","https://openalex.org/W6602002561","https://openalex.org/W6640212811","https://openalex.org/W6713894373","https://openalex.org/W6748159248","https://openalex.org/W6751820410","https://openalex.org/W6752554729","https://openalex.org/W6754087829","https://openalex.org/W6754257133","https://openalex.org/W6754493472","https://openalex.org/W6755207826","https://openalex.org/W6758958943","https://openalex.org/W6763745640","https://openalex.org/W6764146914"],"related_works":["https://openalex.org/W4313814116","https://openalex.org/W4305042383","https://openalex.org/W2546649374","https://openalex.org/W1550318927","https://openalex.org/W4380854332","https://openalex.org/W2184859701","https://openalex.org/W2411269036","https://openalex.org/W2009950829","https://openalex.org/W2769171667","https://openalex.org/W4386232293"],"abstract_inverted_index":{"Textual":[0],"emotion":[1,29,100,112,119,146],"detection":[2],"is":[3,40,55,80,91,115,168],"an":[4,118],"attractive":[5],"task":[6],"while":[7],"previous":[8],"studies":[9],"mainly":[10,56],"focused":[11],"on":[12,143,171],"polarity":[13],"or":[14],"single-emotion":[15],"classification.":[16],"However,":[17],"human":[18],"expressions":[19],"are":[20],"complex,":[21],"and":[22,66,148,159,175],"multiple":[23,83],"emotions":[24,46],"often":[25],"co-occur":[26],"with":[27],"non-negligible":[28],"correlations.":[30],"In":[31],"this":[32,135,194],"paper,":[33],"a":[34,49,98,106,127],"Multi-label":[35],"Emotion":[36,67],"Detection":[37],"Architecture":[38],"(MEDA)":[39],"proposed":[41,165,184],"to":[42,93,103],"detect":[43],"all":[44],"associated":[45],"expressed":[47],"in":[48,89,122,193],"given":[50],"piece":[51],"of":[52,58,82,97,157,164],"text.":[53],"MEDA":[54,71,166],"composed":[57,81],"two":[59],"modules:":[60],"Multi-Channel":[61],"Emotion-Specified":[62],"Feature":[63],"Extractor":[64],"(MC-ESFE)":[65],"Correlation":[68],"Learner":[69],"(ECorL).":[70],"captures":[72],"underlying":[73,110],"emotion-specified":[74],"features":[75],"through":[76,105,117],"MC-ESFE":[77,90],"module,":[78],"which":[79],"channel-wise":[84],"ESFE":[85],"networks.":[86],"Each":[87],"channel":[88],"devoted":[92],"the":[94,138,150,155,183],"feature":[95],"extraction":[96],"specified":[99],"from":[101],"sentence-level":[102],"context-level":[104],"hierarchical":[107],"structure.":[108],"With":[109,134],"features,":[111],"correlation":[113],"learning":[114],"implemented":[116],"sequence":[120],"predictor":[121],"ECorL.":[123],"Furthermore,":[124],"we":[125],"define":[126],"new":[128],"loss":[129,136],"function:":[130],"multi-label":[131],"focal":[132],"loss.":[133],"function,":[137],"model":[139],"can":[140,186],"focus":[141],"more":[142],"misclassified":[144],"positive-negative":[145],"pairs":[147],"improve":[149],"overall":[151],"performance":[152,189],"by":[153],"balancing":[154],"prediction":[156],"positive":[158],"negative":[160],"emotions.":[161],"The":[162,178],"evaluation":[163],"architecture":[167],"carried":[169],"out":[170],"emotional":[172],"corpus:":[173],"RenCECps":[174],"NLPCC2018":[176],"datasets.":[177],"experimental":[179],"results":[180],"indicate":[181],"that":[182],"method":[185],"achieve":[187],"better":[188],"than":[190],"state-of-the-art":[191],"methods":[192],"task.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":30},{"year":2024,"cited_by_count":21},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":11}],"updated_date":"2026-08-29T07:29:34.045763","created_date":"2025-10-10T00:00:00"}
