{"id":"https://openalex.org/W4386435736","doi":"https://doi.org/10.1145/3581783.3611986","title":"Efficient Multi-View Graph Clustering with Local and Global Structure Preservation","display_name":"Efficient Multi-View Graph Clustering with Local and Global Structure Preservation","publication_year":2023,"publication_date":"2023-10-26","ids":{"openalex":"https://openalex.org/W4386435736","doi":"https://doi.org/10.1145/3581783.3611986"},"language":"en","primary_location":{"id":"doi:10.1145/3581783.3611986","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3611986","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2309.00024","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100666914","display_name":"Yi Wen","orcid":"https://orcid.org/0000-0002-5924-1429"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Wen","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102760584","display_name":"Suyuan Liu","orcid":"https://orcid.org/0000-0003-1481-5393"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Suyuan Liu","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091803165","display_name":"Xinhang Wan","orcid":"https://orcid.org/0000-0001-8749-2869"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinhang Wan","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100656645","display_name":"Siwei Wang","orcid":"https://orcid.org/0000-0001-9517-262X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Siwei Wang","raw_affiliation_strings":["Intelligent Game and Decision Lab, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Intelligent Game and Decision Lab, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009525613","display_name":"Ke Liang","orcid":"https://orcid.org/0000-0002-4837-455X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Liang","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101727888","display_name":"Xinwang Liu","orcid":"https://orcid.org/0000-0001-9066-1475"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinwang Liu","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103088081","display_name":"Xihong Yang","orcid":"https://orcid.org/0000-0002-3260-869X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xihong Yang","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025331095","display_name":"Pei Zhang","orcid":"https://orcid.org/0000-0002-3018-5080"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pei Zhang","raw_affiliation_strings":["National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5100666914"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":5.9148,"has_fulltext":true,"cited_by_count":34,"citation_normalized_percentile":{"value":0.97051963,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3021","last_page":"3030"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.993399977684021,"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":0.993399977684021,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.989300012588501,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9860000014305115,"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":0.7985174655914307},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6907972693443298},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5593612790107727},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.4851866364479065},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.48277559876441956},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.47561150789260864},{"id":"https://openalex.org/keywords/clustering-coefficient","display_name":"Clustering coefficient","score":0.4330868124961853},{"id":"https://openalex.org/keywords/graph-partition","display_name":"Graph partition","score":0.42517536878585815},{"id":"https://openalex.org/keywords/local-structure","display_name":"Local structure","score":0.4222426414489746},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30741506814956665},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2020980417728424}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7985174655914307},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6907972693443298},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5593612790107727},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.4851866364479065},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48277559876441956},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.47561150789260864},{"id":"https://openalex.org/C22047676","wikidata":"https://www.wikidata.org/wiki/Q898680","display_name":"Clustering coefficient","level":3,"score":0.4330868124961853},{"id":"https://openalex.org/C48903430","wikidata":"https://www.wikidata.org/wiki/Q491370","display_name":"Graph partition","level":3,"score":0.42517536878585815},{"id":"https://openalex.org/C2986090443","wikidata":"https://www.wikidata.org/wiki/Q77870413","display_name":"Local structure","level":2,"score":0.4222426414489746},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30741506814956665},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2020980417728424},{"id":"https://openalex.org/C159467904","wikidata":"https://www.wikidata.org/wiki/Q2001702","display_name":"Chemical physics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3581783.3611986","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3611986","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2309.00024","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2309.00024","pdf_url":"https://arxiv.org/pdf/2309.00024","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2309.00024","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2309.00024","pdf_url":"https://arxiv.org/pdf/2309.00024","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386435736.pdf","grobid_xml":"https://content.openalex.org/works/W4386435736.grobid-xml"},"referenced_works_count":59,"referenced_works":["https://openalex.org/W1572158434","https://openalex.org/W1965888682","https://openalex.org/W2131828344","https://openalex.org/W2197707282","https://openalex.org/W2199534117","https://openalex.org/W2301166038","https://openalex.org/W2577472518","https://openalex.org/W2741998188","https://openalex.org/W2802754347","https://openalex.org/W2898233200","https://openalex.org/W2903938664","https://openalex.org/W2904419448","https://openalex.org/W2942755646","https://openalex.org/W2955976549","https://openalex.org/W2964378376","https://openalex.org/W2965174731","https://openalex.org/W2997739739","https://openalex.org/W2998004380","https://openalex.org/W2998358581","https://openalex.org/W3005916310","https://openalex.org/W3016050434","https://openalex.org/W3021342796","https://openalex.org/W3025752507","https://openalex.org/W3044063956","https://openalex.org/W3082058021","https://openalex.org/W3083529857","https://openalex.org/W3087257704","https://openalex.org/W3093296731","https://openalex.org/W3117265891","https://openalex.org/W3121769020","https://openalex.org/W3122451732","https://openalex.org/W3136737181","https://openalex.org/W3162780976","https://openalex.org/W3165231040","https://openalex.org/W3205485865","https://openalex.org/W3208823574","https://openalex.org/W3209760397","https://openalex.org/W4212834658","https://openalex.org/W4214493665","https://openalex.org/W4225877894","https://openalex.org/W4226219101","https://openalex.org/W4284965547","https://openalex.org/W4285483676","https://openalex.org/W4298176392","https://openalex.org/W4304098891","https://openalex.org/W4306317449","https://openalex.org/W4312973985","https://openalex.org/W4320713010","https://openalex.org/W4367280449","https://openalex.org/W4382318469","https://openalex.org/W4382466430","https://openalex.org/W6600424091","https://openalex.org/W6600503824","https://openalex.org/W6600599538","https://openalex.org/W6600741150","https://openalex.org/W6601013545","https://openalex.org/W6602990222","https://openalex.org/W6820618299","https://openalex.org/W6825417173"],"related_works":["https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W2948807893","https://openalex.org/W2778153218","https://openalex.org/W1531601525","https://openalex.org/W3139829055","https://openalex.org/W2583811263","https://openalex.org/W3211941742","https://openalex.org/W2035944803"],"abstract_inverted_index":{"Anchor-based":[0],"multi-view":[1,110],"graph":[2,29,111,149],"clustering":[3,99,112,154],"(AMVGC)":[4],"has":[5],"received":[6],"abundant":[7],"attention":[8],"owing":[9],"to":[10,17,69,73,97,136,151],"its":[11],"high":[12],"efficiency":[13,187],"and":[14,121,139,148,174,186],"the":[15,35,40,58,64,75,81,103,153,160,168,178,184],"capability":[16],"capture":[18,137],"complementary":[19],"structural":[20],"information":[21,56],"across":[22],"multiple":[23],"views.":[24],"Intuitively,":[25],"a":[26,107,127,131],"high-quality":[27],"anchor":[28,93,146],"plays":[30],"an":[31,85],"essential":[32],"role":[33],"in":[34,90],"success":[36],"of":[37,163,188],"AMVGC.":[38],"However,":[39],"existing":[41,164],"AMVGC":[42,165],"methods":[43,166],"only":[44],"consider":[45],"single-structure":[46],"information,":[47],"i.e.,":[48],"local":[49,82,138],"or":[50],"global":[51,66,140],"structure,":[52],"which":[53,171],"provides":[54],"insufficient":[55],"for":[57],"learning":[59,150],"task.":[60],"To":[61,101],"be":[62],"specific,":[63],"over-scattered":[65],"structure":[67,83],"leads":[68],"learned":[70],"anchors":[71],"failing":[72],"depict":[74],"cluster":[76],"partition":[77],"well.":[78],"In":[79,156],"contrast,":[80],"with":[84,119,130,177],"improper":[86],"similarity":[87],"measure":[88],"results":[89],"potentially":[91],"inaccurate":[92],"assignment,":[94],"ultimately":[95],"leading":[96],"sub-optimal":[98],"performance.":[100],"tackle":[102],"issue,":[104],"we":[105],"propose":[106],"novel":[108],"anchor-based":[109],"framework":[113,129],"termed":[114],"Efficient":[115],"Multi-View":[116],"Graph":[117],"Clustering":[118],"Local":[120],"Global":[122],"Structure":[123],"Preservation":[124],"(EMVGC-LG).":[125],"Specifically,":[126],"unified":[128],"theoretical":[132],"guarantee":[133],"is":[134,172],"designed":[135],"information.":[141],"Besides,":[142],"EMVGC-LG":[143,158],"jointly":[144],"optimizes":[145],"construction":[147],"enhance":[152],"quality.":[155],"addition,":[157],"inherits":[159],"linear":[161],"complexity":[162],"respecting":[167],"sample":[169],"number,":[170],"time-economical":[173],"scales":[175],"well":[176],"data":[179],"size.":[180],"Extensive":[181],"experiments":[182],"demonstrate":[183],"effectiveness":[185],"our":[189],"proposed":[190],"method.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":13}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}