{"id":"https://openalex.org/W4415541103","doi":"https://doi.org/10.1145/3746027.3754735","title":"DUIMC: Deep Unbalanced Incomplete Multi-View Clustering via Graph Constrained Imputation and Contrastive Learning","display_name":"DUIMC: Deep Unbalanced Incomplete Multi-View Clustering via Graph Constrained Imputation and Contrastive Learning","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415541103","doi":"https://doi.org/10.1145/3746027.3754735"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3754735","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3754735","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","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/A5081114494","display_name":"Wenhui Wu","orcid":"https://orcid.org/0000-0002-0416-7719"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhui Wu","raw_affiliation_strings":["College of Electronics and Information Engineering, Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-0416-7719","affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112605659","display_name":"Guosong Wen","orcid":"https://orcid.org/0009-0001-1447-0279"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanqi Wen","raw_affiliation_strings":["College of Electronics and Information Engineering, Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0001-1447-0279","affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030129372","display_name":"Le Ou-Yang","orcid":"https://orcid.org/0000-0003-4007-4568"},"institutions":[{"id":"https://openalex.org/I4210152380","display_name":"Shenzhen Technology University","ror":"https://ror.org/04qzpec27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152380"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Le Ou-Yang","raw_affiliation_strings":["SMBU-MSU-BIT Joint Laboratory on Bioinformatics and Engineering Biology, Shenzhen MSU-BIT University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-4007-4568","affiliations":[{"raw_affiliation_string":"SMBU-MSU-BIT Joint Laboratory on Bioinformatics and Engineering Biology, Shenzhen MSU-BIT University, Shenzhen, China","institution_ids":["https://openalex.org/I4210152380"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114377922","display_name":"Ran Wang","orcid":"https://orcid.org/0000-0002-2586-5604"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran Wang","raw_affiliation_strings":["School of Artificial Intelligence, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-2586-5604","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008386708","display_name":"Sam Kwong","orcid":"https://orcid.org/0000-0001-7484-7261"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sam Kwong","raw_affiliation_strings":["School of Data Science, Lingnan University, Hong Kong SAR, China"],"raw_orcid":"https://orcid.org/0000-0001-7484-7261","affiliations":[{"raw_affiliation_string":"School of Data Science, Lingnan University, Hong Kong SAR, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"915","last_page":"924"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9979000091552734,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9979000091552734,"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/T10057","display_name":"Face and Expression Recognition","score":0.9962000250816345,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9883000254631042,"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/cluster-analysis","display_name":"Cluster analysis","score":0.7355999946594238},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.6119999885559082},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5681999921798706},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.48260000348091125},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44359999895095825},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40389999747276306},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3874000012874603},{"id":"https://openalex.org/keywords/constrained-clustering","display_name":"Constrained clustering","score":0.35359999537467957}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7355999946594238},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7103000283241272},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6940000057220459},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.6119999885559082},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5681999921798706},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.48260000348091125},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47609999775886536},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44359999895095825},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4163999855518341},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40389999747276306},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3874000012874603},{"id":"https://openalex.org/C27964816","wikidata":"https://www.wikidata.org/wiki/Q5164359","display_name":"Constrained clustering","level":5,"score":0.35359999537467957},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.3483000099658966},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3174999952316284},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.2888999879360199},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.2824999988079071},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.26249998807907104},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3754735","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3754735","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8901588312","display_name":null,"funder_award_id":"62176160, 62173235, 62376162","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1937059634","https://openalex.org/W2134529554","https://openalex.org/W2154478709","https://openalex.org/W2155904486","https://openalex.org/W2181159407","https://openalex.org/W2511630356","https://openalex.org/W2546561608","https://openalex.org/W2766924555","https://openalex.org/W2903938664","https://openalex.org/W2904419448","https://openalex.org/W2914272550","https://openalex.org/W3093207983","https://openalex.org/W3110446398","https://openalex.org/W3110556690","https://openalex.org/W3120213044","https://openalex.org/W3169978599","https://openalex.org/W3203289427","https://openalex.org/W4283798877","https://openalex.org/W4307092192","https://openalex.org/W4312973985","https://openalex.org/W4319878807","https://openalex.org/W4320713010","https://openalex.org/W4362671202","https://openalex.org/W4386071520","https://openalex.org/W4386075537","https://openalex.org/W4388341833","https://openalex.org/W4390685528","https://openalex.org/W4393147606","https://openalex.org/W4393160009","https://openalex.org/W4403791677"],"related_works":[],"abstract_inverted_index":{"Due":[0],"to":[1,60,98,143,161],"the":[2,26,149,164],"frequent":[3],"occurrence":[4],"of":[5],"missing":[6,37],"views":[7],"in":[8,31],"real-world":[9],"multi-view":[10,13,64,122],"data,":[11],"incomplete":[12,29,63],"clustering":[14,65,124,182],"(IMVC)":[15],"has":[16],"attracted":[17],"significant":[18],"attention.":[19],"However,":[20],"most":[21],"existing":[22],"IMVC":[23],"methods":[24,56],"overlook":[25],"fact":[27],"that":[28],"data":[30],"practical":[32],"applications":[33],"often":[34],"exhibits":[35],"varying":[36],"rates":[38],"across":[39],"different":[40],"views,":[41],"rendering":[42],"their":[43,67,72],"mechanisms":[44,160],"ineffective":[45],"under":[46],"such":[47],"conditions.":[48],"Although":[49],"several":[50,185],"works":[51],"based":[52],"on":[53,138,175],"conventional":[54],"learning":[55,103,130,142],"have":[57],"been":[58],"proposed":[59],"solve":[61],"unbalanced":[62,116],"(UIMVC),":[66],"performance":[68,183],"is":[69],"limited":[70],"by":[71,167],"shallow":[73],"feature":[74,150],"representation":[75,129,141],"and":[76,94,118,140,151],"over-sophisticated":[77],"optimization":[78],"procedure.":[79],"In":[80,154],"this":[81],"paper,":[82],"we":[83,156],"propose":[84],"Deep":[85],"Unbalanced":[86],"Incomplete":[87],"Multi-view":[88],"Clustering":[89],"via":[90],"Graph":[91],"Constrained":[92],"Imputation":[93],"Contrastive":[95],"Learning":[96],"(DUIMC)":[97],"address":[99],"UIMVC":[100],"with":[101,121],"deep":[102,128],"paradigm.":[104],"Specifically,":[105],"DUIMC":[106],"introduces":[107],"a":[108,126],"novel":[109],"differentiable":[110],"imputation":[111,139],"layer":[112],"for":[113],"dynamically":[114],"handling":[115],"incompleteness":[117],"integrates":[119],"it":[120],"contrastive":[123],"into":[125],"unified":[127],"framework.":[131],"Furthermore,":[132],"bi-level":[133],"graph":[134],"constraints":[135],"are":[136],"imposed":[137],"preserve":[144],"local":[145],"consistency":[146],"at":[147],"both":[148],"instance":[152],"levels.":[153],"addition,":[155],"develop":[157],"adaptive":[158],"fusion":[159],"adaptively":[162],"restrain":[163],"impact":[165],"aroused":[166],"information":[168],"unbalance":[169],"among":[170],"views.":[171],"Extensive":[172],"experimental":[173],"results":[174],"five":[176],"benchmark":[177],"datasets":[178],"demonstrate":[179],"DUIMC's":[180],"superior":[181],"over":[184],"traditional":[186],"state-of-the-art":[187],"approaches.":[188]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-25T00:00:00"}
