{"id":"https://openalex.org/W4213090352","doi":"https://doi.org/10.1109/tnnls.2022.3147546","title":"Learning Disentangled Representation for Multimodal Cross-Domain Sentiment Analysis","display_name":"Learning Disentangled Representation for Multimodal Cross-Domain Sentiment Analysis","publication_year":2022,"publication_date":"2022-02-21","ids":{"openalex":"https://openalex.org/W4213090352","doi":"https://doi.org/10.1109/tnnls.2022.3147546","pmid":"https://pubmed.ncbi.nlm.nih.gov/35188893"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3147546","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3147546","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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":"Yuhao Zhang","orcid":"https://orcid.org/0000-0002-9856-436X"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuhao Zhang","raw_affiliation_strings":["College of Computer Science, Nankai University, Tianjin, China","Tianjin Key Laboratory of Network and Data Security Technology, College of Cyber Science, Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Network and Data Security Technology, College of Cyber Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ying Zhang","orcid":"https://orcid.org/0000-0003-4906-5828"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Zhang","raw_affiliation_strings":["College of Computer Science, Nankai University, Tianjin, China","Tianjin Key Laboratory of Network and Data Security Technology, College of Cyber Science, Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Network and Data Security Technology, College of Cyber Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wenya Guo","orcid":"https://orcid.org/0000-0001-5609-194X"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenya Guo","raw_affiliation_strings":["College of Computer Science, Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xiangrui Cai","orcid":"https://orcid.org/0000-0001-5039-0922"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangrui Cai","raw_affiliation_strings":["Tianjin Key Laboratory of Network and Data Security Technology, College of Cyber Science, Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Network and Data Security Technology, College of Cyber Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xiaojie Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojie Yuan","raw_affiliation_strings":["Tianjin Key Laboratory of Network and Data Security Technology, College of Cyber Science, Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Network and Data Security Technology, College of Cyber Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I205237279"],"apc_list":null,"apc_paid":null,"fwci":3.1716,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.92599773,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"34","issue":"10","first_page":"7956","last_page":"7966"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.8235999941825867,"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":0.8235999941825867,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.06120000034570694,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.019300000742077827,"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/sentiment-analysis","display_name":"Sentiment analysis","score":0.8500000238418579},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.7386999726295471},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5982999801635742},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5077999830245972},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5055000185966492},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5052000284194946},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.5044999718666077}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.8500000238418579},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.781000018119812},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.7386999726295471},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6651999950408936},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5982999801635742},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5493999719619751},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5077999830245972},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5055000185966492},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5052000284194946},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.5044999718666077},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4625999927520752},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.43549999594688416},{"id":"https://openalex.org/C2776445246","wikidata":"https://www.wikidata.org/wiki/Q1792644","display_name":"Style (visual arts)","level":2,"score":0.42660000920295715},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.375900000333786},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3073999881744385},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.28999999165534973},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2506999969482422},{"id":"https://openalex.org/C2780910867","wikidata":"https://www.wikidata.org/wiki/Q1952416","display_name":"Multimodality","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3147546","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3147546","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:35188893","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35188893","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W359818833","https://openalex.org/W1509250914","https://openalex.org/W1731081199","https://openalex.org/W1904892614","https://openalex.org/W2008635359","https://openalex.org/W2048783874","https://openalex.org/W2084046180","https://openalex.org/W2086277751","https://openalex.org/W2106277773","https://openalex.org/W2110700950","https://openalex.org/W2122563357","https://openalex.org/W2125865219","https://openalex.org/W2128837546","https://openalex.org/W2131953535","https://openalex.org/W2146338426","https://openalex.org/W2158108973","https://openalex.org/W2159570078","https://openalex.org/W2170414372","https://openalex.org/W2214409633","https://openalex.org/W2250539671","https://openalex.org/W2251292973","https://openalex.org/W2265228180","https://openalex.org/W2265846598","https://openalex.org/W2293177440","https://openalex.org/W2397331935","https://openalex.org/W2565799927","https://openalex.org/W2587177071","https://openalex.org/W2593768305","https://openalex.org/W2604737966","https://openalex.org/W2619383789","https://openalex.org/W2740751204","https://openalex.org/W2753840835","https://openalex.org/W2757016771","https://openalex.org/W2773004715","https://openalex.org/W2786808285","https://openalex.org/W2798984401","https://openalex.org/W2808610848","https://openalex.org/W2885719698","https://openalex.org/W2892946488","https://openalex.org/W2897482938","https://openalex.org/W2905562398","https://openalex.org/W2905587047","https://openalex.org/W2910191085","https://openalex.org/W2919206487","https://openalex.org/W2943360842","https://openalex.org/W2963992782","https://openalex.org/W2964008635","https://openalex.org/W2964010806","https://openalex.org/W2964285681","https://openalex.org/W3003963580","https://openalex.org/W3043529747","https://openalex.org/W3094277917","https://openalex.org/W3152368098","https://openalex.org/W3175444644","https://openalex.org/W4205184193","https://openalex.org/W4251372957","https://openalex.org/W6605727216","https://openalex.org/W6633949838","https://openalex.org/W6636510571","https://openalex.org/W6637373629","https://openalex.org/W6639480849","https://openalex.org/W6683633756","https://openalex.org/W6688248365","https://openalex.org/W6738394178"],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"cross-domain":[1,72,132],"sentiment":[2,8,57,73,95,112,121,133],"analysis":[3,134],"aims":[4],"at":[5],"transferring":[6],"domain-invariant":[7],"information":[9,96,122],"across":[10],"datasets":[11,40],"to":[12,62],"address":[13],"the":[14,27,35,47,64,79,84,98,120,138],"insufficiency":[15],"of":[16,31,38,67],"labeled":[17],"data.":[18],"Existing":[19],"adaptation":[20,48],"methods":[21],"achieve":[22],"well":[23],"performance":[24],"by":[25,107],"remitting":[26],"discrepancies":[28],"in":[29],"characteristics":[30],"multiple":[32,80],"modalities.":[33],"However,":[34],"expressive":[36,68,105],"styles":[37,69],"different":[39,125],"also":[41],"contain":[42],"domain-specific":[43,104],"information,":[44],"which":[45,116],"hinders":[46],"performance.":[49],"In":[50],"this":[51],"article,":[52],"we":[53,76,93],"propose":[54],"a":[55,88],"disentangled":[56],"representation":[58,86,101,113],"adversarial":[59,108],"network":[60],"(DiSRAN)":[61],"reduce":[63],"domain":[65],"shift":[66],"for":[70],"multimodal":[71,99,131],"analysis.":[74],"Specifically,":[75],"first":[77],"align":[78],"modalities":[81],"and":[82],"obtain":[83],"joint":[85,100],"through":[87],"cross-modality":[89],"attention":[90],"layer.":[91],"Then,":[92],"disentangle":[94],"from":[97],"that":[102,137],"contains":[103],"style":[106],"training.":[109],"The":[110],"obtained":[111],"is":[114],"domain-invariant,":[115],"can":[117],"better":[118],"facilitate":[119],"transfer":[123],"between":[124],"domains.":[126],"Experimental":[127],"results":[128],"on":[129],"two":[130],"tasks":[135],"demonstrate":[136],"proposed":[139],"method":[140],"performs":[141],"favorably":[142],"against":[143],"state-of-the-art":[144],"approaches.":[145]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2022-02-24T00:00:00"}