{"id":"https://openalex.org/W4403791644","doi":"https://doi.org/10.1145/3664647.3681163","title":"KEBR: Knowledge Enhanced Self-Supervised Balanced Representation for Multimodal Sentiment Analysis","display_name":"KEBR: Knowledge Enhanced Self-Supervised Balanced Representation for Multimodal Sentiment Analysis","publication_year":2024,"publication_date":"2024-10-26","ids":{"openalex":"https://openalex.org/W4403791644","doi":"https://doi.org/10.1145/3664647.3681163"},"language":"en","primary_location":{"id":"doi:10.1145/3664647.3681163","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3681163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","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/A5034288582","display_name":"Aoqiang Zhu","orcid":"https://orcid.org/0000-0002-2452-6862"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Aoqiang Zhu","raw_affiliation_strings":["Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091586702","display_name":"Min Hu","orcid":"https://orcid.org/0000-0003-2122-0240"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Hu","raw_affiliation_strings":["Hefei University of Technology, Hefei, Anhui, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei, Anhui, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066988252","display_name":"Xiaohua Wang","orcid":"https://orcid.org/0000-0003-1751-2291"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohua Wang","raw_affiliation_strings":["Hefei University of Technology, Hefei, Anhui, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei, Anhui, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079824167","display_name":"Jiaoyun Yang","orcid":"https://orcid.org/0000-0002-0233-590X"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaoyun Yang","raw_affiliation_strings":["Hefei University of Technology, Hefei, Anhui, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei, Anhui, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108053572","display_name":"Yiming Tang","orcid":"https://orcid.org/0000-0002-0917-2277"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiming Tang","raw_affiliation_strings":["Hefei University of Technology, Hefei, Anhui, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei, Anhui, China","institution_ids":["https://openalex.org/I16365422"]}]},{"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/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuji Ren","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5034288582"],"corresponding_institution_ids":["https://openalex.org/I16365422"],"apc_list":null,"apc_paid":null,"fwci":2.0851,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.89187598,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5732","last_page":"5741"},"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/T10028","display_name":"Topic Modeling","score":0.9986000061035156,"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":0.9976000189781189,"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":0.7306103706359863},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.6402548551559448},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5418236255645752},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5174942016601562},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.43808993697166443},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3519102931022644}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7306103706359863},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6402548551559448},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5418236255645752},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5174942016601562},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.43808993697166443},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3519102931022644},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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:10.1145/3664647.3681163","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3681163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","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":46,"referenced_works":["https://openalex.org/W2099813784","https://openalex.org/W2191779130","https://openalex.org/W2251394420","https://openalex.org/W2465534249","https://openalex.org/W2619383789","https://openalex.org/W2726515241","https://openalex.org/W2787581402","https://openalex.org/W2807126412","https://openalex.org/W2896457183","https://openalex.org/W2916104401","https://openalex.org/W2949391930","https://openalex.org/W2950635152","https://openalex.org/W2953356739","https://openalex.org/W2958722525","https://openalex.org/W2964010806","https://openalex.org/W2964121744","https://openalex.org/W2964216663","https://openalex.org/W2964346351","https://openalex.org/W2965373594","https://openalex.org/W2998385486","https://openalex.org/W3034266838","https://openalex.org/W3034854575","https://openalex.org/W3035333188","https://openalex.org/W3035419191","https://openalex.org/W3035668167","https://openalex.org/W3037572520","https://openalex.org/W3090716330","https://openalex.org/W3093051361","https://openalex.org/W3093400813","https://openalex.org/W3128412859","https://openalex.org/W3159683831","https://openalex.org/W3214432797","https://openalex.org/W4221141990","https://openalex.org/W4221152594","https://openalex.org/W4285184319","https://openalex.org/W4292958273","https://openalex.org/W4301104990","https://openalex.org/W4304091726","https://openalex.org/W4312639100","https://openalex.org/W4372260352","https://openalex.org/W4376226279","https://openalex.org/W4382603208","https://openalex.org/W4385245566","https://openalex.org/W4385570908","https://openalex.org/W4385570923","https://openalex.org/W4389047389"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Multimodal":[0],"sentiment":[1,128,135,139],"analysis":[2],"(MSA)":[3],"aims":[4],"to":[5,11,93,109,119],"integrate":[6],"multiple":[7],"modalities":[8],"of":[9,35,44,51,91,98,113,127],"information":[10,83,115],"better":[12],"understand":[13],"human":[14],"sentiment.":[15],"The":[16],"current":[17],"research":[18],"mainly":[19],"focuses":[20],"on":[21],"conducting":[22],"multimodal":[23,96,102],"fusion,":[24],"which":[25,79],"neglects":[26],"the":[27,33,42,48,57,81,85,88,95,111,121,125,148],"under-optimized":[28],"modal":[29],"representations":[30],"generated":[31],"by":[32],"imbalance":[34],"unimodal":[36],"performances":[37],"in":[38,116],"joint":[39,117],"learning.":[40],"Moreover,":[41],"size":[43],"labeled":[45],"datasets":[46],"limits":[47],"generalization":[49],"ability":[50],"existing":[52],"supervised":[53],"models.":[54],"To":[55],"address":[56],"above":[58],"issues,":[59],"this":[60],"paper":[61],"proposes":[62],"a":[63,71,101],"knowledge-enhanced":[64],"self-supervised":[65],"balanced":[66],"representation":[67,90,97],"approach":[68],"(KEBR).":[69],"First,":[70],"text-based":[72],"cross-modal":[73],"fusion":[74,112],"method":[75],"(TCMF)":[76],"is":[77,107],"constructed,":[78],"injects":[80],"non-verbal":[82,114,131],"from":[84],"videos":[86],"into":[87],"semantic":[89],"text":[92],"enhance":[94],"text.":[99],"Then,":[100],"cosine":[103],"constrained":[104],"loss":[105],"(MCC)":[106],"designed":[108],"constrain":[110],"learning":[118],"balance":[120],"representation.":[122],"Finally,":[123],"with":[124],"help":[126],"knowledge":[129],"and":[130,138],"information,":[132],"KEBR":[133,146],"conducts":[134],"word":[136],"masking":[137],"intensity":[140],"prediction.":[141],"Experimental":[142],"results":[143],"show":[144],"that":[145],"outperforms":[147],"baseline.":[149]},"counts_by_year":[{"year":2025,"cited_by_count":6}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}