{"id":"https://openalex.org/W3214949568","doi":"https://doi.org/10.1109/tbdata.2021.3131707","title":"Identification of Communities With Multi-Semantics via Bayesian Generative Model","display_name":"Identification of Communities With Multi-Semantics via Bayesian Generative Model","publication_year":2021,"publication_date":"2021-12-01","ids":{"openalex":"https://openalex.org/W3214949568","doi":"https://doi.org/10.1109/tbdata.2021.3131707","mag":"3214949568"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2021.3131707","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2021.3131707","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"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 Big 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/A5009013876","display_name":"Dongxiao He","orcid":"https://orcid.org/0000-0002-1915-4179"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dongxiao He","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103055985","display_name":"Yanli Wu","orcid":"https://orcid.org/0000-0003-3952-7005"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanli Wu","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047853850","display_name":"Youyou Wang","orcid":"https://orcid.org/0000-0003-1251-4829"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youyou Wang","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065948939","display_name":"Zhizhi Yu","orcid":"https://orcid.org/0000-0001-5954-3593"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhizhi Yu","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100736532","display_name":"Zhiyong Feng","orcid":"https://orcid.org/0000-0001-8158-7453"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyong Feng","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103015888","display_name":"Xiaobao Wang","orcid":"https://orcid.org/0000-0001-5086-4964"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaobao Wang","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103195106","display_name":"Yuxiao Huang","orcid":"https://orcid.org/0000-0001-9394-805X"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]},{"id":"https://openalex.org/I4210158842","display_name":"GW Medical Faculty Associates","ror":"https://ror.org/02bn3v102","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210158842"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuxiao Huang","raw_affiliation_strings":["Columbian College of Arts &#x0026; Sciences, George Washington University, Washington, DC, USA"],"affiliations":[{"raw_affiliation_string":"Columbian College of Arts &#x0026; Sciences, George Washington University, Washington, DC, USA","institution_ids":["https://openalex.org/I193531525","https://openalex.org/I4210158842"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5009013876"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":0.5259,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.65763464,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"8","issue":"4","first_page":"869","last_page":"881"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":1.0,"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":1.0,"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/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9983999729156494,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.8478131294250488},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8392563462257385},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.7478839755058289},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6392037272453308},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5881794095039368},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5686083436012268},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5468775629997253},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.49913811683654785},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4935246706008911},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.47981691360473633},{"id":"https://openalex.org/keywords/interpretation","display_name":"Interpretation (philosophy)","score":0.47093573212623596},{"id":"https://openalex.org/keywords/semantic-interpretation","display_name":"Semantic interpretation","score":0.4615170657634735},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4523318111896515},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3686302900314331},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.36140504479408264}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8478131294250488},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8392563462257385},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.7478839755058289},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6392037272453308},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5881794095039368},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5686083436012268},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5468775629997253},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.49913811683654785},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4935246706008911},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.47981691360473633},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.47093573212623596},{"id":"https://openalex.org/C193125573","wikidata":"https://www.wikidata.org/wiki/Q7449065","display_name":"Semantic interpretation","level":2,"score":0.4615170657634735},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4523318111896515},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3686302900314331},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.36140504479408264},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tbdata.2021.3131707","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2021.3131707","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"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 Big Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6134627929","display_name":null,"funder_award_id":"61832014","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G678178878","display_name":null,"funder_award_id":"61876128","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8451749416","display_name":null,"funder_award_id":"61772361","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W565269975","https://openalex.org/W1872749931","https://openalex.org/W1963502056","https://openalex.org/W1971421925","https://openalex.org/W2012921801","https://openalex.org/W2059047669","https://openalex.org/W2104819583","https://openalex.org/W2111315907","https://openalex.org/W2112439948","https://openalex.org/W2119998616","https://openalex.org/W2120043163","https://openalex.org/W2132368295","https://openalex.org/W2139694940","https://openalex.org/W2153959628","https://openalex.org/W2165636119","https://openalex.org/W2225156818","https://openalex.org/W2406185338","https://openalex.org/W2411855254","https://openalex.org/W2416738288","https://openalex.org/W2524865061","https://openalex.org/W2604745395","https://openalex.org/W2611491469","https://openalex.org/W2613261984","https://openalex.org/W2755088640","https://openalex.org/W2771332840","https://openalex.org/W2809645418","https://openalex.org/W2887415938","https://openalex.org/W2910559764","https://openalex.org/W2912917402","https://openalex.org/W2951271819","https://openalex.org/W2965819445","https://openalex.org/W2972607219","https://openalex.org/W2995460050","https://openalex.org/W3008313157","https://openalex.org/W3017112682","https://openalex.org/W3026423472","https://openalex.org/W3035665545","https://openalex.org/W3102647957","https://openalex.org/W3126033509","https://openalex.org/W3155044266","https://openalex.org/W3155886566","https://openalex.org/W3164338400","https://openalex.org/W3183749514","https://openalex.org/W3194841521","https://openalex.org/W4212863985","https://openalex.org/W4237791300","https://openalex.org/W6687780494","https://openalex.org/W6744271739","https://openalex.org/W6756248755","https://openalex.org/W6763813028"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4395044357","https://openalex.org/W4287117424","https://openalex.org/W4387506531","https://openalex.org/W2087346071","https://openalex.org/W2967848559","https://openalex.org/W4299831724"],"abstract_inverted_index":{"Discovering":[0],"communities":[1,44,60],"is":[2,110],"an":[3,70],"essential":[4],"step":[5],"in":[6,69,165],"the":[7,28,40,56,63,90,100,148,155,159],"analysis":[8],"of":[9,27,43,58,66,143,158,167,176],"complex":[10],"systems,":[11],"and":[12,21,61,89,95,151,169],"it":[13],"has":[14,45],"two":[15,81,105],"purposes:":[16],"to":[17,22,114,120],"identify":[18,36],"functional":[19],"modules":[20,67],"interpret":[23],"semantics.":[24],"However,":[25],"most":[26],"existing":[29,163],"community":[30,87,123,177],"detection":[31,178],"methods":[32,164],"only":[33,112],"focused":[34,54],"on":[35,55,147],"communities,":[37,116],"while":[38],"learning":[39,62],"semantics":[41,64,96],"interpretation":[42,65],"not":[46,111],"been":[47],"fully":[48],"studied.":[49],"In":[50],"this":[51],"paper,":[52],"we":[53,134],"problem":[57],"identifying":[59],"jointly":[68],"end-to-end":[71],"model.":[72],"We":[73,171],"designed":[74],"a":[75,122,136,140,181,185],"novel":[76],"generative":[77],"model":[78,132],"which":[79],"combines":[80],"closely":[82],"related":[83],"parts,":[84,106],"one":[85,127],"for":[86,92,131],"discovery":[88],"other":[91],"content":[93],"clustering":[94],"interpretation.":[97],"By":[98],"extracting":[99],"potential":[101],"correlation":[102],"between":[103],"these":[104],"our":[107],"new":[108],"method":[109],"robust":[113],"discovering":[115],"but":[117],"also":[118,172],"able":[119],"provide":[121],"with":[124],"more":[125],"than":[126],"semantic":[128,174],"topic.":[129],"As":[130],"inference,":[133],"developed":[135],"variational":[137],"algorithm":[138],"from":[139],"Bayesian":[141],"point":[142],"view.":[144],"Experimental":[145],"results":[146,179],"artificial":[149],"benchmark":[150],"real":[152],"networks":[153],"showed":[154],"superior":[156],"performance":[157],"proposed":[160],"approach":[161],"over":[162,184],"terms":[166],"effectiveness":[168],"efficiency.":[170],"analyzed":[173],"interpretability":[175],"through":[180],"case":[182],"study":[183],"large-scale":[186],"music":[187],"platform":[188],"dataset.":[189]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
