{"id":"https://openalex.org/W4293187595","doi":"https://doi.org/10.1145/3532612","title":"Individuality Meets Commonality: A Unified Graph Learning Framework for Multi-View Clustering","display_name":"Individuality Meets Commonality: A Unified Graph Learning Framework for Multi-View Clustering","publication_year":2022,"publication_date":"2022-04-27","ids":{"openalex":"https://openalex.org/W4293187595","doi":"https://doi.org/10.1145/3532612"},"language":"en","primary_location":{"id":"doi:10.1145/3532612","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3532612","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","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/A5080192610","display_name":"Zhibin Gu","orcid":"https://orcid.org/0000-0002-1085-9084"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhibin Gu","raw_affiliation_strings":["School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-1085-9084","affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085406955","display_name":"Songhe Feng","orcid":"https://orcid.org/0000-0002-5922-9358"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Songhe Feng","raw_affiliation_strings":["School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5922-9358","affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":1.837,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.87415865,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"17","issue":"1","first_page":"1","last_page":"21"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9955999851226807,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9955999851226807,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9916999936103821,"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/cluster-analysis","display_name":"Cluster analysis","score":0.8090816140174866},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7516050338745117},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5060996413230896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47273412346839905},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4498594403266907},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40575453639030457},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3431667387485504}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8090816140174866},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7516050338745117},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5060996413230896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47273412346839905},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4498594403266907},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40575453639030457},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3431667387485504}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3532612","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3532612","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2744622150","display_name":"\u5f31\u76d1\u7763\u5b66\u4e60\u6846\u67b6\u4e0b\u5927\u89c4\u6a21\u56fe\u50cf\u8bed\u4e49\u7406\u89e3\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61872032","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1508044906","https://openalex.org/W1538422756","https://openalex.org/W1583837637","https://openalex.org/W1993962865","https://openalex.org/W1997201895","https://openalex.org/W2014288923","https://openalex.org/W2121947440","https://openalex.org/W2151103935","https://openalex.org/W2163352848","https://openalex.org/W2531563875","https://openalex.org/W2615217854","https://openalex.org/W2753064086","https://openalex.org/W2757686304","https://openalex.org/W2761674588","https://openalex.org/W2783863635","https://openalex.org/W2801999749","https://openalex.org/W2891953767","https://openalex.org/W2893652381","https://openalex.org/W2895210058","https://openalex.org/W2896169497","https://openalex.org/W2898541610","https://openalex.org/W2914393402","https://openalex.org/W2914552685","https://openalex.org/W2914761779","https://openalex.org/W2921065608","https://openalex.org/W2943996654","https://openalex.org/W2997969890","https://openalex.org/W2998358581","https://openalex.org/W3004244740","https://openalex.org/W3024343454","https://openalex.org/W3044063956","https://openalex.org/W3118054267","https://openalex.org/W3120689699","https://openalex.org/W3128918602","https://openalex.org/W3134487894","https://openalex.org/W3140079845","https://openalex.org/W3151867486","https://openalex.org/W3163957165","https://openalex.org/W3165231040","https://openalex.org/W3197466146","https://openalex.org/W3205512245","https://openalex.org/W4220873374","https://openalex.org/W4236965008","https://openalex.org/W4248003669","https://openalex.org/W4301409532","https://openalex.org/W6795611471"],"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":{"Multi-view":[0],"clustering,":[1,81],"which":[2,50,82,142],"aims":[3],"at":[4],"boosting":[5],"the":[6,11,15,38,45,54,85,89,104,108,112,125,132,150,165],"clustering":[7,32,153,173],"performance":[8],"by":[9],"leveraging":[10],"individual":[12],"information":[13,17,56],"and":[14,71,88,111,119,131],"common":[16],"of":[18,49,128,167],"multi-view":[19,31,39,46,80,86,90,117],"data,":[20],"has":[21],"gained":[22],"extensive":[23],"consideration":[24],"in":[25],"recent":[26],"years.":[27],"However,":[28],"most":[29],"existing":[30],"algorithms":[33],"either":[34],"focus":[35],"on":[36,43,160],"extracting":[37],"individuality":[40,87],"or":[41],"emphasize":[42],"exploring":[44],"commonality,":[47],"neither":[48],"can":[51],"fully":[52],"utilize":[53],"comprehensive":[55],"from":[57,115],"multiple":[58],"views.":[59],"To":[60,101],"this":[61],"end,":[62],"we":[63],"propose":[64],"a":[65,93,146],"novel":[66],"algorithm":[67],"named":[68],"V":[69],"iew-specific":[70],"C":[72],"onsensus":[73],"G":[74],"raph":[75],"A":[76],"lignment":[77],"(VCGA)":[78],"for":[79,155],"simultaneously":[83],"formulates":[84],"commonality":[91],"into":[92,137],"unified":[94],"framework":[95],"to":[96,149],"effectively":[97],"partition":[98],"data":[99,118],"points.":[100],"be":[102],"specific,":[103],"VCGA":[105],"model":[106],"constructs":[107],"view-specific":[109,126],"graphs":[110,127],"shared":[113],"graph":[114,134],"original":[116],"hidden":[120],"latent":[121],"representation,":[122],"respectively.":[123],"Furthermore,":[124],"different":[129],"views":[130],"consensus":[133],"are":[135],"aligned":[136],"an":[138],"informative":[139],"target":[140],"graph,":[141],"is":[143],"employed":[144],"as":[145],"crucial":[147],"input":[148],"standard":[151],"spectral":[152],"method":[154,169],"clustering.":[156],"Extensive":[157],"experimental":[158],"results":[159],"six":[161],"benchmark":[162],"datasets":[163],"demonstrate":[164],"superiority":[166],"our":[168],"against":[170],"other":[171],"state-of-the-art":[172],"algorithms.":[174]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}