{"id":"https://openalex.org/W4403791782","doi":"https://doi.org/10.1145/3664647.3681030","title":"Learning Dual Enhanced Representation for Contrastive Multi-view Clustering","display_name":"Learning Dual Enhanced Representation for Contrastive Multi-view Clustering","publication_year":2024,"publication_date":"2024-10-26","ids":{"openalex":"https://openalex.org/W4403791782","doi":"https://doi.org/10.1145/3664647.3681030"},"language":"en","primary_location":{"id":"doi:10.1145/3664647.3681030","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3681030","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":"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/A5047981777","display_name":"Guoliang Zou","orcid":"https://orcid.org/0000-0002-6633-4711"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoliang Zou","raw_affiliation_strings":["Zhengzhou University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-6633-4711","affiliations":[{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045940041","display_name":"Yangdong Ye","orcid":"https://orcid.org/0000-0001-7027-8313"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yangdong Ye","raw_affiliation_strings":["Zhengzhou University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-7027-8313","affiliations":[{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036449771","display_name":"Tongji Chen","orcid":"https://orcid.org/0009-0006-6785-0888"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tongji Chen","raw_affiliation_strings":["Zhengzhou University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0009-0006-6785-0888","affiliations":[{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078088762","display_name":"Shizhe Hu","orcid":"https://orcid.org/0000-0003-1301-2396"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shizhe Hu","raw_affiliation_strings":["Zhengzhou University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-1301-2396","affiliations":[{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I38877650"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"8731","last_page":"8739"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9993000030517578,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9993000030517578,"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/T10057","display_name":"Face and Expression Recognition","score":0.998199999332428,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9962999820709229,"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":0.7004292011260986},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.6615414023399353},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.659031093120575},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5164570808410645},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5000464916229248},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3580351769924164},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32364141941070557},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.08419531583786011}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7004292011260986},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.6615414023399353},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.659031093120575},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5164570808410645},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5000464916229248},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3580351769924164},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32364141941070557},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.08419531583786011},{"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3664647.3681030","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3681030","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":24,"referenced_works":["https://openalex.org/W2155904486","https://openalex.org/W2740464254","https://openalex.org/W2790108222","https://openalex.org/W2790770303","https://openalex.org/W2965624713","https://openalex.org/W3044096495","https://openalex.org/W3160988939","https://openalex.org/W3217784147","https://openalex.org/W4304080225","https://openalex.org/W4304092341","https://openalex.org/W4312280106","https://openalex.org/W4317743260","https://openalex.org/W4377000374","https://openalex.org/W4377710637","https://openalex.org/W4378804891","https://openalex.org/W4385128132","https://openalex.org/W4387675711","https://openalex.org/W4387968141","https://openalex.org/W4387968160","https://openalex.org/W4387969777","https://openalex.org/W4388194748","https://openalex.org/W4388968015","https://openalex.org/W4391341369","https://openalex.org/W4391853581"],"related_works":["https://openalex.org/W4298130764","https://openalex.org/W2804364458","https://openalex.org/W2132641928","https://openalex.org/W4310225030","https://openalex.org/W2090259340","https://openalex.org/W1926736923","https://openalex.org/W2158836806","https://openalex.org/W2393816671","https://openalex.org/W2083665254","https://openalex.org/W2942177010"],"abstract_inverted_index":{"Contrastive":[0,91],"multi-view":[1,248],"clustering":[2,142,193],"is":[3,45,74,138,265],"widely":[4],"recognized":[5],"for":[6,90],"its":[7],"effectiveness":[8],"in":[9,22,57,83,182,201],"mining":[10,59],"feature":[11,62,127],"representation":[12],"across":[13],"views":[14,131,181],"via":[15],"contrastive":[16],"learning":[17,157],"(CL),":[18],"gaining":[19],"significant":[20],"attention":[21],"recent":[23],"years.":[24],"Most":[25],"existing":[26,197],"methods":[27,198,234],"mainly":[28,103],"focus":[29],"on":[30,156,247],"the":[31,48,68,78,98,141,152,164,168,175,184,191,202,206,209,215,222,227,236,252],"feature-level":[32,43,109],"or/and":[33],"cluster-level":[34,65,114,210],"CL,":[35],"but":[36],"there":[37],"are":[38,160,239],"still":[39],"two":[40,105],"shortcomings.":[41],"Firstly,":[42],"CL":[44,66,110,115],"limited":[46],"by":[47,77,213],"influence":[49],"of":[50,60,70,170,179,189,235],"anomalies":[51],"and":[52,73,101,112,132,173,221,242],"large":[53],"noise":[54],"data,":[55,166],"resulting":[56],"insufficient":[58],"discriminative":[61,177],"representation.":[63],"Secondly,":[64],"lacks":[67],"guidance":[69],"global":[71],"information":[72,136,178,207],"always":[75],"restricted":[76],"local":[79],"diversity":[80],"information.":[81],"We":[82],"this":[84],"paper":[85],"Learn":[86],"dUal":[87],"enhanCed":[88],"rEpresentation":[89],"Multi-view":[92],"Clustering":[93],"(LUCE-CMC)":[94],"to":[95,124,140,150,154,162,258],"effectively":[96],"addresses":[97],"above":[99],"challenges,":[100],"it":[102],"contains":[104],"parts,":[106],"i.e.,":[107],"enhanced":[108,113],"(En-FeaCL)":[111],"(En-CluCL).":[116],"Specifically,":[117],"we":[118,145,200],"first":[119],"adopt":[120],"a":[121,147,259],"shared":[122,126,228],"encoder":[123],"learn":[125],"representations":[128],"between":[129],"multiple":[130],"then":[133],"obtain":[134],"cluster-relevant":[135],"that":[137,159,251],"beneficial":[139],"results.":[143],"Moreover,":[144],"design":[146],"reconstitution":[148],"approach":[149],"force":[151],"model":[153,238],"concentrate":[155],"features":[158],"critical":[161],"reconstructing":[163],"input":[165],"reducing":[167],"impact":[169],"noisy":[171],"data":[172],"maximizing":[174],"sufficient":[176],"different":[180],"helping":[183],"En-FeaCL":[185],"part.":[186],"Finally,":[187],"instead":[188],"contrasting":[190,214],"view-specific":[192],"result":[194],"like":[195],"most":[196],"do,":[199],"En-CluCL":[203],"part":[204],"make":[205],"at":[208,267],"more":[211],"richer":[212],"cluster":[216,223],"assignment":[217,224],"from":[218,226],"each":[219],"view":[220],"obtained":[225],"fused":[229],"features.":[230],"The":[231,262],"end-to-end":[232],"training":[233],"proposed":[237,253],"mutually":[240],"reinforcing":[241],"beneficial.":[243],"Extensive":[244],"experiments":[245],"conducted":[246],"datasets":[249],"show":[250],"LUCE-CMC":[254],"outperforms":[255],"established":[256],"baselines":[257],"considerable":[260],"extent.":[261],"source":[263],"code":[264],"released":[266],"https://github.com/ShizheHu.":[268]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
