{"id":"https://openalex.org/W3091879728","doi":"https://doi.org/10.1109/tkde.2020.3029582","title":"Distributed Bayesian Matrix Decomposition for Big Data Mining and Clustering","display_name":"Distributed Bayesian Matrix Decomposition for Big Data Mining and Clustering","publication_year":2020,"publication_date":"2020-10-08","ids":{"openalex":"https://openalex.org/W3091879728","doi":"https://doi.org/10.1109/tkde.2020.3029582","mag":"3091879728"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2020.3029582","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2020.3029582","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/A5056069816","display_name":"Chihao Zhang","orcid":"https://orcid.org/0000-0002-2135-5690"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210095018","display_name":"National Center for Mathematics and Interdisciplinary Sciences","ror":"https://ror.org/00s97k668","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210095018"]},{"id":"https://openalex.org/I4210120485","display_name":"Academy of Mathematics and Systems Science","ror":"https://ror.org/02jkmyk67","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210120485"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chihao Zhang","raw_affiliation_strings":["NCMIS, CEMS, RCSDS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China","Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China","School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"NCMIS, CEMS, RCSDS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210120485","https://openalex.org/I4210095018","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113746317","display_name":"Yang Yang","orcid":"https://orcid.org/0009-0005-6715-7912"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Yang","raw_affiliation_strings":["School of Software, Yunnan University, Kunming, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Yunnan University, Kunming, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051349066","display_name":"Wei Zhou","orcid":"https://orcid.org/0000-0002-5881-9436"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhou","raw_affiliation_strings":["School of Software, Yunnan University, Kunming, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Yunnan University, Kunming, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076619069","display_name":"Shihua Zhang","orcid":"https://orcid.org/0000-0003-0192-7118"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210095018","display_name":"National Center for Mathematics and Interdisciplinary Sciences","ror":"https://ror.org/00s97k668","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210095018"]},{"id":"https://openalex.org/I4210120485","display_name":"Academy of Mathematics and Systems Science","ror":"https://ror.org/02jkmyk67","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210120485"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shihua Zhang","raw_affiliation_strings":["NCMIS, CEMS, RCSDS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China","Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China","School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"NCMIS, CEMS, RCSDS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210120485","https://openalex.org/I4210095018","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5056069816"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210095018","https://openalex.org/I4210120485","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.9144,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.74721968,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"34","issue":"8","first_page":"3701","last_page":"3713"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9958000183105469,"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":0.8338010311126709},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.814145028591156},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6116205453872681},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5780860185623169},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5770859718322754},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5426992774009705},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.4121176600456238},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2721053957939148},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.255509614944458}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8338010311126709},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.814145028591156},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6116205453872681},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5780860185623169},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5770859718322754},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5426992774009705},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.4121176600456238},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2721053957939148},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.255509614944458},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2020.3029582","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2020.3029582","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/G3523307272","display_name":null,"funder_award_id":"61621003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5538595313","display_name":null,"funder_award_id":"61762089","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8325739885","display_name":null,"funder_award_id":"11661141019","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":53,"referenced_works":["https://openalex.org/W312962489","https://openalex.org/W410850256","https://openalex.org/W1495241813","https://openalex.org/W1670132599","https://openalex.org/W1902027874","https://openalex.org/W1970625287","https://openalex.org/W2031696998","https://openalex.org/W2038559942","https://openalex.org/W2059745395","https://openalex.org/W2068548513","https://openalex.org/W2077442640","https://openalex.org/W2085040216","https://openalex.org/W2100556411","https://openalex.org/W2101893470","https://openalex.org/W2105622852","https://openalex.org/W2108119513","https://openalex.org/W2108399535","https://openalex.org/W2109761160","https://openalex.org/W2111312248","https://openalex.org/W2116216716","https://openalex.org/W2117968640","https://openalex.org/W2125027820","https://openalex.org/W2136468592","https://openalex.org/W2153622543","https://openalex.org/W2165685007","https://openalex.org/W2167686991","https://openalex.org/W2222512263","https://openalex.org/W2294798173","https://openalex.org/W2315452447","https://openalex.org/W2405459681","https://openalex.org/W2594404444","https://openalex.org/W2743795536","https://openalex.org/W2949755237","https://openalex.org/W2958550196","https://openalex.org/W2962825295","https://openalex.org/W2963855576","https://openalex.org/W2964231067","https://openalex.org/W2966006719","https://openalex.org/W2980192021","https://openalex.org/W3023496898","https://openalex.org/W3101078587","https://openalex.org/W3194313756","https://openalex.org/W4212863985","https://openalex.org/W4254223024","https://openalex.org/W4292363360","https://openalex.org/W6614148910","https://openalex.org/W6636883489","https://openalex.org/W6640396632","https://openalex.org/W6668990524","https://openalex.org/W6674595457","https://openalex.org/W6680770193","https://openalex.org/W6681623065","https://openalex.org/W6696835939"],"related_works":["https://openalex.org/W4390608645","https://openalex.org/W4247566972","https://openalex.org/W4394895745","https://openalex.org/W2960264696","https://openalex.org/W3090563135","https://openalex.org/W2497432351","https://openalex.org/W4206777497","https://openalex.org/W2910064364","https://openalex.org/W4200136508","https://openalex.org/W2499527417"],"abstract_inverted_index":{"Matrix":[0],"decomposition":[1,67,101],"is":[2,20,59],"one":[3],"of":[4,131,145,152,166],"the":[5,80,85,117,122,127,136,141,150,153,164,167],"fundamental":[6],"tools":[7],"to":[8,25,63,115,185,195],"discover":[9],"knowledge":[10],"from":[11],"big":[12,28,39,69,105,186],"data":[13,29,40,52,70,106,187],"generated":[14],"by":[15],"modern":[16],"applications.":[17],"However,":[18],"it":[19],"still":[21],"inefficient":[22],"or":[23,191],"infeasible":[24],"process":[26],"very":[27],"using":[30],"such":[31,51],"a":[32,35,73,89,97],"method":[33,74,130],"in":[34,88],"single":[36],"machine.":[37],"Moreover,":[38],"are":[41],"often":[42],"distributedly":[43],"collected":[44],"and":[45,61,83,108,134,175,188,202],"stored":[46],"on":[47],"different":[48],"machines.":[49],"Thus,":[50],"generally":[53],"bear":[54],"strong":[55],"heterogeneous":[56,81],"noise.":[57],"It":[58],"essential":[60],"useful":[62],"develop":[64],"distributed":[65,90,98,118,198],"matrix":[66,100],"for":[68,104],"analytics.":[71],"Such":[72],"should":[75],"scale":[76,182],"up":[77,183],"well,":[78],"model":[79,102],"noise,":[82,154],"address":[84,149],"communication":[86],"issue":[87],"system.":[91],"To":[92,148],"this":[93],"end,":[94],"we":[95,111,155],"propose":[96,156],"Bayesian":[99],"(DBMD)":[103],"mining":[107],"clustering.":[109],"Specifically,":[110],"adopt":[112],"three":[113],"strategies":[114],"implement":[116],"computing":[119],"including":[120,200],"1)":[121],"accelerated":[123],"gradient":[124],"descent,":[125],"2)":[126],"alternating":[128],"direction":[129],"multipliers":[132],"(ADMM),":[133],"3)":[135],"statistical":[137],"inference.":[138],"We":[139],"investigate":[140],"theoretical":[142,173],"convergence":[143],"behaviors":[144],"these":[146],"algorithms.":[147],"heterogeneity":[151],"an":[157],"optimal":[158],"plug-in":[159],"weighted":[160],"average":[161],"that":[162,179],"reduces":[163],"variance":[165],"estimation.":[168],"Synthetic":[169],"experiments":[170,177],"validate":[171],"our":[172,180],"results,":[174],"real-world":[176],"show":[178],"algorithms":[181],"well":[184],"achieves":[189],"superior":[190],"competing":[192],"performance":[193],"compared":[194],"two":[196],"typical":[197],"methods":[199],"Scalable-NMF":[201],"scalable":[203],"k-means++.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}