{"id":"https://openalex.org/W4410414884","doi":"https://doi.org/10.1177/18724981251338268","title":"Multimedia emotion representation analysis based on graph convolution adversarial learning and attention mechanism","display_name":"Multimedia emotion representation analysis based on graph convolution adversarial learning and attention mechanism","publication_year":2025,"publication_date":"2025-05-14","ids":{"openalex":"https://openalex.org/W4410414884","doi":"https://doi.org/10.1177/18724981251338268"},"language":"en","primary_location":{"id":"doi:10.1177/18724981251338268","is_oa":false,"landing_page_url":"https://doi.org/10.1177/18724981251338268","pdf_url":null,"source":{"id":"https://openalex.org/S119727669","display_name":"Intelligent Decision Technologies","issn_l":"1872-4981","issn":["1872-4981","1875-8843"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Decision Technologies","raw_type":"journal-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":null,"display_name":"Yanmei Tian","orcid":"https://orcid.org/0009-0008-8891-1293"},"institutions":[{"id":"https://openalex.org/I95004497","display_name":"Hebei Institute of Physical Education","ror":"https://ror.org/024ba6473","country_code":"CN","type":"education","lineage":["https://openalex.org/I95004497"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanmei Tian","raw_affiliation_strings":["Psychological Health Service Center, Hebei Vocational College of Rail Transportation, Shijiazhuang, 050000, China"],"raw_orcid":"https://orcid.org/0009-0008-8891-1293","affiliations":[{"raw_affiliation_string":"Psychological Health Service Center, Hebei Vocational College of Rail Transportation, Shijiazhuang, 050000, China","institution_ids":["https://openalex.org/I95004497"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100557479","display_name":"Zhu Meng","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Meng Zhu","raw_affiliation_strings":["Students\u2019 Affairs Division, Hebei Vocational College of Rail Transportation, Shijiazhuang, 050000, China"],"raw_orcid":"https://orcid.org/0009-0000-0339-1842","affiliations":[{"raw_affiliation_string":"Students\u2019 Affairs Division, Hebei Vocational College of Rail Transportation, Shijiazhuang, 050000, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100557479"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0787399,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":"4","first_page":"2064","last_page":"2085"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11439","display_name":"Video Analysis and Summarization","score":0.9847000241279602,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10667","display_name":"Emotion and Mood Recognition","score":0.9842000007629395,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.69968581199646},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.666682243347168},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.641373872756958},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6237744092941284},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6219062805175781},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5619391798973083},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4455104470252991},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40297362208366394},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.3740287721157074},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.35894930362701416},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3396289348602295},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.23978838324546814},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.11226317286491394}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.69968581199646},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.666682243347168},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.641373872756958},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6237744092941284},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6219062805175781},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5619391798973083},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4455104470252991},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40297362208366394},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.3740287721157074},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.35894930362701416},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3396289348602295},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.23978838324546814},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11226317286491394},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1177/18724981251338268","is_oa":false,"landing_page_url":"https://doi.org/10.1177/18724981251338268","pdf_url":null,"source":{"id":"https://openalex.org/S119727669","display_name":"Intelligent Decision Technologies","issn_l":"1872-4981","issn":["1872-4981","1875-8843"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Decision Technologies","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W2901063069","https://openalex.org/W2979368787","https://openalex.org/W3000139089","https://openalex.org/W3014475539","https://openalex.org/W3022569189","https://openalex.org/W3038315208","https://openalex.org/W3095937012","https://openalex.org/W3107569791","https://openalex.org/W3130062726","https://openalex.org/W3154382135","https://openalex.org/W3159950750","https://openalex.org/W3159952799","https://openalex.org/W3164156840","https://openalex.org/W3202700139","https://openalex.org/W3216921303","https://openalex.org/W4206615250","https://openalex.org/W4210347936","https://openalex.org/W4210611093","https://openalex.org/W4225611164","https://openalex.org/W4226068530","https://openalex.org/W4280571589","https://openalex.org/W4280582835","https://openalex.org/W4281802316","https://openalex.org/W4283021663","https://openalex.org/W4283076857","https://openalex.org/W4283366946","https://openalex.org/W4286640379","https://openalex.org/W4288802276","https://openalex.org/W4293235175","https://openalex.org/W4295113529","https://openalex.org/W4295308310","https://openalex.org/W4306746108","https://openalex.org/W4307647225","https://openalex.org/W4312316493","https://openalex.org/W4313639160","https://openalex.org/W4321022102","https://openalex.org/W4321482228","https://openalex.org/W4377861913","https://openalex.org/W4379619596","https://openalex.org/W4388966595"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W4285226279","https://openalex.org/W4288019534"],"abstract_inverted_index":{"Technological":[0],"progress":[1],"has":[2,66],"driven":[3],"the":[4,38,70,125,161,165,170,203,215],"vigorous":[5],"development":[6],"of":[7,13,40,45,69,73,140,169,184,192,234,243],"multimedia":[8,14,29,49,64,108,127,171,251],"technology,":[9],"with":[10,202,227],"massive":[11],"amounts":[12],"data":[15,186,253,269],"generated":[16],"every":[17],"moment.":[18],"Efficient":[19],"sentiment":[20],"analysis":[21],"algorithms":[22],"can":[23],"help":[24],"people":[25],"understand":[26],"and":[27,33,36,100,117,144,149,158,160,179,196,224,237,258,265,271],"use":[28],"data,":[30],"reduce":[31],"production":[32],"management":[34],"costs,":[35],"improve":[37],"efficiency":[39],"human-computer":[41],"interaction.":[42],"The":[43,152,189,248],"extraction":[44,225],"emotional":[46,61,80,198,231,252,268,272],"features":[47,81,257],"from":[48,63,254],"information":[50,74,86,98,222,232],"is":[51],"a":[52,94,107],"crucial":[53],"step":[54],"in":[55,85,93,221,230],"capturing":[56],"semantic":[57],"information.":[58],"Accurately":[59],"extracting":[60,79],"states":[62],"content":[65,99,273],"become":[67],"one":[68],"important":[71,262],"focuses":[72],"processing.":[75],"Traditional":[76],"methods":[77],"for":[78,147,267],"have":[82],"limited":[83],"accuracy":[84,191],"disclosure":[87],"due":[88],"to":[89],"their":[90],"singularity,":[91],"resulting":[92],"significant":[95],"gap":[96],"between":[97],"actual":[101],"cognition.":[102],"To":[103],"address":[104],"this":[105],"issue,":[106],"emotion":[109,128,134,142,172],"representation":[110,135,223],"method":[111,123],"combining":[112],"graph":[113],"convolutional":[114],"adversarial":[115,138],"learning":[116],"attention":[118,145],"mechanism":[119],"was":[120,156,175],"proposed.":[121],"This":[122],"achieved":[124],"final":[126],"design":[129,139],"model":[130,155],"by":[131],"constructing":[132],"an":[133,228,238],"feature":[136],"model,":[137],"multidimensional":[141],"labels,":[143,259],"modules":[146],"local":[148],"overall":[150,239],"emotions.":[151],"proposed":[153],"hybrid":[154,217],"tested":[157],"analyzed,":[159],"results":[162],"showed":[163],"that":[164],"average":[166,240],"loss":[167],"value":[168,205,264],"fusion":[173],"algorithm":[174,218],"less":[176,244],"than":[177,210,245],"0.3,":[178],"its":[180],"accurate":[181],"recognition":[182,190],"rate":[183],"video":[185],"reached":[187],"90.47%.":[188],"neutral,":[193],"angry,":[194],"happy,":[195],"sad":[197],"labels":[199],"exceeded":[200],"85%,":[201],"highest":[204],"reaching":[206],"92.30%,":[207],"significantly":[208],"better":[209,220],"other":[211],"algorithms.":[212],"In":[213],"addition,":[214],"improved":[216],"performed":[219],"capabilities,":[226],"increase":[229],"interactivity":[233],"over":[235],"40%":[236],"time":[241],"consumption":[242],"1.5":[246],"s.":[247],"study":[249],"analyzes":[250],"two":[255],"dimensions:":[256],"effectively":[260],"providing":[261],"research":[263],"significance":[266],"mining":[270],"capture.":[274]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}