{"id":"https://openalex.org/W4287887113","doi":"https://doi.org/10.1109/tkde.2022.3192686","title":"Latent Representation Guided Multi-View Clustering","display_name":"Latent Representation Guided Multi-View Clustering","publication_year":2022,"publication_date":"2022-07-25","ids":{"openalex":"https://openalex.org/W4287887113","doi":"https://doi.org/10.1109/tkde.2022.3192686"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2022.3192686","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3192686","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","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":"https://openalex.org/A5101577578","display_name":"Shudong Huang","orcid":"https://orcid.org/0000-0002-1276-8696"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shudong Huang","raw_affiliation_strings":["College of Computer Science, Sichuan University, Chengdu, China","College of Computer Science, Sichuan University, Chengdu, P. R. China"],"raw_orcid":"https://orcid.org/0000-0002-1276-8696","affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"]},{"raw_affiliation_string":"College of Computer Science, Sichuan University, Chengdu, P. R. China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ivor W. Tsang","orcid":"https://orcid.org/0000-0003-2211-8176"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ivor W. Tsang","raw_affiliation_strings":["Centre for Artificial Intelligence, FEIT, University of Technology Sydney, Sydney, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0003-2211-8176","affiliations":[{"raw_affiliation_string":"Centre for Artificial Intelligence, FEIT, University of Technology Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051227924","display_name":"Zenglin Xu","orcid":"https://orcid.org/0000-0001-5550-6461"},"institutions":[{"id":"https://openalex.org/I158809036","display_name":"Shenzhen Institute of Information Technology","ror":"https://ror.org/03wrf9427","country_code":"CN","type":"education","lineage":["https://openalex.org/I158809036"]},{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zenglin Xu","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology Shenzhen, Shenzhen, China","School of Computer Science and Technology, Harbin Institute of Technology Shenzhen, Shenzhen, P. R. China"],"raw_orcid":"https://orcid.org/0000-0001-5550-6461","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology Shenzhen, Shenzhen, China","institution_ids":["https://openalex.org/I158809036","https://openalex.org/I204983213"]},{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology Shenzhen, Shenzhen, P. R. China","institution_ids":["https://openalex.org/I158809036","https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073535763","display_name":"Jiancheng Lv","orcid":"https://orcid.org/0000-0001-6551-3884"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiancheng Lv","raw_affiliation_strings":["College of Computer Science, Sichuan University, Chengdu, China","College of Computer Science, Sichuan University, Chengdu, P. R. China"],"raw_orcid":"https://orcid.org/0000-0001-6551-3884","affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"]},{"raw_affiliation_string":"College of Computer Science, Sichuan University, Chengdu, P. R. China","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4577,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.82345923,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"35","issue":"7","first_page":"7082","last_page":"7087"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9987999796867371,"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":0.9987999796867371,"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":0.9983999729156494,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9970999956130981,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7389018535614014},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6735109090805054},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5366052985191345},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5294700860977173},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.500295877456665},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.48889556527137756},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47487661242485046},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41894668340682983},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2643049657344818}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7389018535614014},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6735109090805054},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5366052985191345},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5294700860977173},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.500295877456665},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.48889556527137756},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47487661242485046},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41894668340682983},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2643049657344818},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2022.3192686","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3192686","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1515513899","display_name":null,"funder_award_id":"62106164","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5347934389","display_name":null,"funder_award_id":"B21044","funder_id":"https://openalex.org/F4320327912","funder_display_name":"Higher Education Discipline Innovation Project"},{"id":"https://openalex.org/G6846722749","display_name":null,"funder_award_id":"61836006","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"},{"id":"https://openalex.org/F4320327912","display_name":"Higher Education Discipline Innovation Project","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1550614472","https://openalex.org/W1566135517","https://openalex.org/W1857382374","https://openalex.org/W1907775068","https://openalex.org/W1975172027","https://openalex.org/W1979089718","https://openalex.org/W2002469984","https://openalex.org/W2043545458","https://openalex.org/W2049585407","https://openalex.org/W2108119513","https://openalex.org/W2117228865","https://openalex.org/W2138019504","https://openalex.org/W2161969291","https://openalex.org/W2170798597","https://openalex.org/W2187089797","https://openalex.org/W2577472518","https://openalex.org/W2584959193","https://openalex.org/W2604723872","https://openalex.org/W2740464254","https://openalex.org/W2756626360","https://openalex.org/W2787523326","https://openalex.org/W2788811707","https://openalex.org/W2803341107","https://openalex.org/W2808465901","https://openalex.org/W2809506935","https://openalex.org/W2896169497","https://openalex.org/W2900980272","https://openalex.org/W2913653723","https://openalex.org/W2921065608","https://openalex.org/W2940933409","https://openalex.org/W2964378376","https://openalex.org/W3118054267","https://openalex.org/W3151867486","https://openalex.org/W4230962939","https://openalex.org/W4281719469","https://openalex.org/W6675134712","https://openalex.org/W6678739253","https://openalex.org/W6682991666","https://openalex.org/W6731811539","https://openalex.org/W6762833281"],"related_works":["https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W2357409937","https://openalex.org/W2510582230","https://openalex.org/W2978674666","https://openalex.org/W2074430941","https://openalex.org/W2113096305","https://openalex.org/W1977636359","https://openalex.org/W2772305933","https://openalex.org/W2580722822"],"abstract_inverted_index":{"Multi-view":[0],"clustering":[1],"aims":[2,147],"to":[3,69,95,105,123,131,191],"reveal":[4],"the":[5,28,100,111,117,124,129,181,193,203,206],"correlation":[6],"between":[7,16],"different":[8],"input":[9],"modalities":[10],"in":[11,162],"an":[12],"unsupervised":[13],"way.":[14],"Similarity":[15],"data":[17,133],"samples":[18],"can":[19,135,173],"be":[20,136,174],"described":[21],"by":[22,177],"a":[23,66,72,89,107,143,163],"similarity":[24,41,75,82,101,155],"graph,":[25],"which":[26,47],"governs":[27],"quality":[29],"of":[30,113,116,205],"multi-view":[31,35,79],"clustering.":[32,80],"However,":[33],"existing":[34],"graph":[36,42,76,83,102,119,156],"learning":[37],"methods":[38],"mainly":[39],"construct":[40],"based":[43,87],"on":[44,88,198],"raw":[45],"features,":[46],"are":[48,169],"unreliable":[49],"as":[50],"real-world":[51],"datasets":[52,201],"usually":[53],"contain":[54,106],"noises,":[55],"outliers,":[56],"or":[57],"even":[58],"redundant":[59],"information.":[60],"In":[61],"this":[62],"paper,":[63],"we":[64],"formulate":[65],"novel":[67],"model":[68,146],"simultaneously":[70],"learn":[71],"robust":[73],"structured":[74],"and":[77,97,158,172],"perform":[78],"The":[81],"is":[84,93,103,120,189],"adaptively":[85],"learned":[86],"latent":[90,152],"representation":[91,153],"that":[92],"invulnerable":[94],"noises":[96],"outliers.":[98],"Furthermore,":[99],"enforced":[104],"clear":[108],"structure,":[109],"i.e.,":[110],"number":[112],"connected":[114],"components":[115],"target":[118],"exactly":[121],"equal":[122],"ground-truth":[125],"class":[126],"number.":[127],"Consequently,":[128],"label":[130,160],"each":[132,178],"sample":[134],"directly":[137],"assigned":[138],"without":[139],"any":[140],"postprocessing.":[141],"As":[142],"result,":[144],"our":[145],"at":[148],"accomplishing":[149],"three":[150,167],"subtasks:":[151],"extraction,":[154],"learning,":[157],"cluster":[159],"allocation,":[161],"unified":[164],"framework.":[165],"These":[166],"subtasks":[168],"seamlessly":[170],"integrated":[171],"mutually":[175],"boosted":[176],"other":[179],"towards":[180],"overall":[182],"optimal":[183],"solution.":[184],"An":[185],"efficient":[186],"alternation":[187],"algorithm":[188],"proposed":[190,207],"solve":[192],"optimization":[194],"problem.":[195],"Experimental":[196],"results":[197],"several":[199],"benchmark":[200],"illustrate":[202],"effectiveness":[204],"model.":[208]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}