{"id":"https://openalex.org/W2255966421","doi":"https://doi.org/10.1109/tkde.2015.2492565","title":"Fast Online EM for Big Topic Modeling","display_name":"Fast Online EM for Big Topic Modeling","publication_year":2015,"publication_date":"2015-10-20","ids":{"openalex":"https://openalex.org/W2255966421","doi":"https://doi.org/10.1109/tkde.2015.2492565","mag":"2255966421"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2015.2492565","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2015.2492565","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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1210.2179","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062026103","display_name":"Jia Zeng","orcid":"https://orcid.org/0000-0001-9980-492X"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jia Zeng","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100415118","display_name":"Zhiqiang Liu","orcid":"https://orcid.org/0000-0003-2135-8581"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zhi-Qiang Liu","raw_affiliation_strings":["School of Creative Media, City University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"School of Creative Media, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100851247","display_name":"Xiao-Qin Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xiao-Qin Cao","raw_affiliation_strings":["School of Creative Media, City University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"School of Creative Media, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5062026103"],"corresponding_institution_ids":["https://openalex.org/I3923682"],"apc_list":null,"apc_paid":null,"fwci":4.4662,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.95051534,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"28","issue":"3","first_page":"675","last_page":"688"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9998000264167786,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9998000264167786,"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/T10028","display_name":"Topic Modeling","score":0.9976000189781189,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.992900013923645,"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/computer-science","display_name":"Computer science","score":0.8194456696510315},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.7576054334640503},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.7123970985412598},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5722480416297913},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5556485652923584},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.5309032201766968},{"id":"https://openalex.org/keywords/likelihood-function","display_name":"Likelihood function","score":0.414264440536499},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35125958919525146},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3386954665184021},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.28550559282302856},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.19457054138183594},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.1798172891139984},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10042968392372131}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8194456696510315},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.7576054334640503},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.7123970985412598},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5722480416297913},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5556485652923584},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.5309032201766968},{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.414264440536499},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35125958919525146},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3386954665184021},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28550559282302856},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.19457054138183594},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.1798172891139984},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10042968392372131},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tkde.2015.2492565","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2015.2492565","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"},{"id":"pmh:oai:arXiv.org:1210.2179","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1210.2179","pdf_url":"https://arxiv.org/pdf/1210.2179","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1210.2179","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1210.2179","pdf_url":"https://arxiv.org/pdf/1210.2179","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1074596136","display_name":null,"funder_award_id":"61272449","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2100336016","display_name":null,"funder_award_id":"7008026","funder_id":"https://openalex.org/F4320309893","funder_display_name":"City University of Hong Kong"},{"id":"https://openalex.org/G3714835486","display_name":null,"funder_award_id":"9041574","funder_id":"https://openalex.org/F4320321592","funder_display_name":"Research Grants Council, University Grants Committee"},{"id":"https://openalex.org/G6443257668","display_name":null,"funder_award_id":"61033013","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6665959330","display_name":null,"funder_award_id":"61373092","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8023373932","display_name":null,"funder_award_id":"61572339","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306709","display_name":"Glaucoma Research Foundation","ror":"https://ror.org/05ez53b31"},{"id":"https://openalex.org/F4320309893","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321592","display_name":"Research Grants Council, University Grants Committee","ror":"https://ror.org/00djwmt25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W86282824","https://openalex.org/W150620477","https://openalex.org/W1503398984","https://openalex.org/W1518708866","https://openalex.org/W1546359014","https://openalex.org/W1659337733","https://openalex.org/W1686266550","https://openalex.org/W1880262756","https://openalex.org/W1905496962","https://openalex.org/W1991255919","https://openalex.org/W1994616650","https://openalex.org/W2001082470","https://openalex.org/W2001975024","https://openalex.org/W2008225289","https://openalex.org/W2009966364","https://openalex.org/W2049633694","https://openalex.org/W2052261215","https://openalex.org/W2053193751","https://openalex.org/W2106316877","https://openalex.org/W2116137244","https://openalex.org/W2119072456","https://openalex.org/W2130428211","https://openalex.org/W2134731454","https://openalex.org/W2135790056","https://openalex.org/W2138996412","https://openalex.org/W2144100511","https://openalex.org/W2146341620","https://openalex.org/W2150731624","https://openalex.org/W2158919786","https://openalex.org/W2161353674","https://openalex.org/W2165599843","https://openalex.org/W2171278750","https://openalex.org/W2174706414","https://openalex.org/W2197869238","https://openalex.org/W2567948266","https://openalex.org/W2949205689","https://openalex.org/W2950413897","https://openalex.org/W2950770596","https://openalex.org/W2951681883","https://openalex.org/W4231510805","https://openalex.org/W4294377911","https://openalex.org/W6630941500","https://openalex.org/W6639619044","https://openalex.org/W6639766741","https://openalex.org/W6675830456","https://openalex.org/W6677121468","https://openalex.org/W6678901940","https://openalex.org/W6683543995","https://openalex.org/W6683847445","https://openalex.org/W6684489972","https://openalex.org/W6764125297"],"related_works":["https://openalex.org/W2888805565","https://openalex.org/W4312773271","https://openalex.org/W4315588616","https://openalex.org/W2769501189","https://openalex.org/W2962686197","https://openalex.org/W2207653751","https://openalex.org/W4293863151","https://openalex.org/W3159709618","https://openalex.org/W2611137333","https://openalex.org/W3005513013"],"abstract_inverted_index":{"The":[0],"expectation-maximization":[1],"(EM)":[2],"algorithm":[3,73],"can":[4,98],"compute":[5],"the":[6,17,34,42,76,80,90,101,106,114,121,136],"maximum-likelihood":[7],"(ML)":[8],"or":[9,20],"maximum":[10],"a":[11,68,155],"posterior":[12],"(MAP)":[13],"point":[14,104],"estimate":[15],"of":[16,33,105],"mixture":[18],"models":[19,23,58,148],"latent":[21,26],"variable":[22],"such":[24],"as":[25],"Dirichlet":[27],"allocation":[28],"(LDA),which":[29],"has":[30,48],"been":[31],"one":[32],"most":[35],"popular":[36],"probabilistic":[37],"topic":[38,77,132,151],"modeling":[39,133],"methods":[40],"in":[41],"past":[43],"decade.":[44],"However,":[45],"batch":[46],"EM":[47,71],"high":[49],"time":[50],"and":[51,117,146],"space":[52],"complexities":[53],"to":[54,100,141],"learn":[55],"big":[56,60,144,147,150],"LDA":[57,139],"from":[59,79],"data":[61,145],"streams.":[62],"In":[63],"this":[64],"paper,":[65],"we":[66,94],"present":[67],"fast":[69,115],"online":[70,138],"(FOEM)":[72],"that":[74,96],"infers":[75],"distribution":[78],"previously":[81],"unseen":[82],"documents":[83],"incrementally":[84],"with":[85],"constant":[86],"memory":[87,123],"requirements.":[88],"Within":[89],"stochastic":[91],"approximation":[92],"framework,":[93],"show":[95],"FOEM":[97,125],"converge":[99],"local":[102],"stationary":[103],"LDA's":[107],"likelihood":[108],"function.":[109],"By":[110],"dynamic":[111],"scheduling":[112],"for":[113,120,129],"speed":[116],"parameter":[118],"streaming":[119],"low":[122],"usage,":[124],"is":[126],"more":[127],"efficient":[128],"some":[130],"lifelong":[131],"tasks":[134],"than":[135],"state-of-the-art":[137],"algorithms":[140],"handle":[142],"both":[143],"(aka,":[149],"modeling)":[152],"on":[153],"just":[154],"PC.":[156]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":5}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
