{"id":"https://openalex.org/W2111315907","doi":"https://doi.org/10.1145/2213836.2213894","title":"A model-based approach to attributed graph clustering","display_name":"A model-based approach to attributed graph clustering","publication_year":2012,"publication_date":"2012-05-20","ids":{"openalex":"https://openalex.org/W2111315907","doi":"https://doi.org/10.1145/2213836.2213894","mag":"2111315907"},"language":"en","primary_location":{"id":"doi:10.1145/2213836.2213894","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2213836.2213894","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data","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/A5101799658","display_name":"Zhiqiang Xu","orcid":"https://orcid.org/0000-0002-5693-8933"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Zhiqiang Xu","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore","Nanyang Technological University, Singapore, SINGAPORE#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Nanyang Technological University, Singapore, SINGAPORE#TAB#","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074491217","display_name":"Yiping Ke","orcid":"https://orcid.org/0000-0001-9473-3202"},"institutions":[{"id":"https://openalex.org/I3004594783","display_name":"Institute of High Performance Computing","ror":"https://ror.org/02n0ejh50","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3004594783","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yiping Ke","raw_affiliation_strings":["Institute of High Performance Computing, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of High Performance Computing, Singapore, Singapore","institution_ids":["https://openalex.org/I3004594783"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100375975","display_name":"Yi Wang","orcid":"https://orcid.org/0000-0001-8534-6868"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yi Wang","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101984697","display_name":"Hong Cheng","orcid":"https://orcid.org/0000-0002-4673-2587"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Hong Cheng","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016082884","display_name":"James Cheng","orcid":"https://orcid.org/0000-0001-6313-6288"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"James Cheng","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore","Nanyang Technological University, Singapore, SINGAPORE#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Nanyang Technological University, Singapore, SINGAPORE#TAB#","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":13.3449,"has_fulltext":false,"cited_by_count":338,"citation_normalized_percentile":{"value":0.98934945,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"505","last_page":"516"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998000264167786,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9962000250816345,"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":0.9961000084877014,"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":0.8116434812545776},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7155876159667969},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5635194182395935},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5613732933998108},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4988234043121338},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4923182725906372},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4892747104167938},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.42252790927886963},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.416969358921051},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.33200979232788086},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32467877864837646}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8116434812545776},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7155876159667969},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5635194182395935},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5613732933998108},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4988234043121338},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4923182725906372},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4892747104167938},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.42252790927886963},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.416969358921051},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33200979232788086},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32467877864837646}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/2213836.2213894","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2213836.2213894","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.231.4767","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.231.4767","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.se.cuhk.edu.hk/%7Eypke/BAGC_sigmod12.pdf","raw_type":"text"},{"id":"pmh:oai:dr.ntu.edu.sg:10356/98766","is_oa":false,"landing_page_url":"http://hdl.handle.net/10220/12623","pdf_url":null,"source":{"id":"https://openalex.org/S4306402609","display_name":"DR-NTU (Nanyang Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I172675005","host_organization_name":"Nanyang Technological University","host_organization_lineage":["https://openalex.org/I172675005"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W19224017","https://openalex.org/W61587124","https://openalex.org/W1516111018","https://openalex.org/W1568436970","https://openalex.org/W1972386210","https://openalex.org/W1993591232","https://openalex.org/W2026859125","https://openalex.org/W2089458547","https://openalex.org/W2095293504","https://openalex.org/W2095867140","https://openalex.org/W2099111195","https://openalex.org/W2107743791","https://openalex.org/W2133299088","https://openalex.org/W2135827982","https://openalex.org/W2149587453","https://openalex.org/W2159080219","https://openalex.org/W2165515835","https://openalex.org/W2170875403","https://openalex.org/W4233135949"],"related_works":["https://openalex.org/W4379251913","https://openalex.org/W1999117613","https://openalex.org/W2040929534","https://openalex.org/W3022637481","https://openalex.org/W2393816671","https://openalex.org/W3120229345","https://openalex.org/W2804957450","https://openalex.org/W3144143113","https://openalex.org/W2111119584","https://openalex.org/W3039964395"],"abstract_inverted_index":{"Graph":[0],"clustering,":[1],"also":[2],"known":[3],"as":[4],"community":[5],"detection,":[6],"is":[7],"a":[8,40,47,71,80,90,103,111,123],"long-standing":[9],"problem":[10],"in":[11,25],"data":[12],"mining.":[13],"However,":[14],"with":[15,115],"the":[16,107,116,147],"proliferation":[17],"of":[18,102,110],"rich":[19],"attribute":[20,33,59,100],"information":[21,34],"available":[22],"for":[23,35,84,95,127],"objects":[24],"real-world":[26,139],"graphs,":[27],"how":[28],"to":[29,55,74],"leverage":[30],"structural":[31,57,98],"and":[32,58,69,92,99],"clustering":[36,152],"attributed":[37,75,85,150],"graphs":[38],"becomes":[39],"new":[41],"challenge.":[42],"Most":[43],"existing":[44],"works":[45],"take":[46],"distance-based":[48,149],"approach.":[49],"They":[50],"proposed":[51,117],"various":[52],"distance":[53,112],"measures":[54],"combine":[56],"information.":[60],"In":[61],"this":[62],"paper,":[63],"we":[64,129],"consider":[65],"an":[66,131],"alternative":[67],"view":[68],"propose":[70],"model-based":[72],"approach":[73],"graph":[76,151],"clustering.":[77],"We":[78],"develop":[79],"Bayesian":[81],"probabilistic":[82,124],"model":[83,88,118],"graphs.":[86],"The":[87],"provides":[89],"principled":[91],"natural":[93],"framework":[94],"capturing":[96],"both":[97],"aspects":[101],"graph,":[104],"while":[105],"avoiding":[106],"artificial":[108],"design":[109],"measure.":[113],"Clustering":[114],"can":[119],"be":[120],"transformed":[121],"into":[122],"inference":[125],"problem,":[126],"which":[128],"devise":[130],"efficient":[132],"variational":[133],"algorithm.":[134],"Experimental":[135],"results":[136],"on":[137],"large":[138],"datasets":[140],"demonstrate":[141],"that":[142],"our":[143],"method":[144],"significantly":[145],"outperforms":[146],"state-of-art":[148],"method.":[153]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":24},{"year":2021,"cited_by_count":36},{"year":2020,"cited_by_count":46},{"year":2019,"cited_by_count":37},{"year":2018,"cited_by_count":35},{"year":2017,"cited_by_count":38},{"year":2016,"cited_by_count":27},{"year":2015,"cited_by_count":25},{"year":2014,"cited_by_count":17},{"year":2013,"cited_by_count":12},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}