{"id":"https://openalex.org/W2803895891","doi":"https://doi.org/10.1155/2018/2503816","title":"CLDA: An Effective Topic Model for Mining User Interest Preference under Big Data Background","display_name":"CLDA: An Effective Topic Model for Mining User Interest Preference under Big Data Background","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2803895891","doi":"https://doi.org/10.1155/2018/2503816","mag":"2803895891"},"language":"en","primary_location":{"id":"doi:10.1155/2018/2503816","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2018/2503816","pdf_url":"http://downloads.hindawi.com/journals/complexity/2018/2503816.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"http://downloads.hindawi.com/journals/complexity/2018/2503816.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024600603","display_name":"Lirong Qiu","orcid":"https://orcid.org/0000-0001-6489-1648"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lirong Qiu","raw_affiliation_strings":["School of Information Engineering, Minzu University of China, Beijing, China","School of Information Engineering, Minzu University of China, Beijing"],"raw_orcid":"https://orcid.org/0000-0001-6489-1648","affiliations":[{"raw_affiliation_string":"School of Information Engineering, Minzu University of China, Beijing, China","institution_ids":["https://openalex.org/I145897649"]},{"raw_affiliation_string":"School of Information Engineering, Minzu University of China, Beijing","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101858289","display_name":"Jia Yu","orcid":"https://orcid.org/0000-0002-4556-1413"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jia Yu","raw_affiliation_strings":["School of Information Engineering, Minzu University of China, Beijing, China","School of Information Engineering, Minzu University of China, Beijing"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Minzu University of China, Beijing, China","institution_ids":["https://openalex.org/I145897649"]},{"raw_affiliation_string":"School of Information Engineering, Minzu University of China, Beijing","institution_ids":["https://openalex.org/I145897649"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5024600603"],"corresponding_institution_ids":["https://openalex.org/I145897649"],"apc_list":{"value":2300,"currency":"USD","value_usd":2300},"apc_paid":{"value":2300,"currency":"USD","value_usd":2300},"fwci":2.4161,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.91469379,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"2018","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9916999936103821,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.991100013256073,"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/microblogging","display_name":"Microblogging","score":0.8886314630508423},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.8774495124816895},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8245950937271118},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.7383338809013367},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.6703973412513733},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6681606769561768},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5639240145683289},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5447349548339844},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5147840976715088},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.49354851245880127},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.49034643173217773},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4688369333744049},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4290599822998047},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42165786027908325},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.24826639890670776}],"concepts":[{"id":"https://openalex.org/C143275388","wikidata":"https://www.wikidata.org/wiki/Q92438","display_name":"Microblogging","level":3,"score":0.8886314630508423},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.8774495124816895},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8245950937271118},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.7383338809013367},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.6703973412513733},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6681606769561768},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5639240145683289},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5447349548339844},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5147840976715088},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.49354851245880127},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.49034643173217773},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4688369333744049},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4290599822998047},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42165786027908325},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.24826639890670776},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.0},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1155/2018/2503816","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2018/2503816","pdf_url":"http://downloads.hindawi.com/journals/complexity/2018/2503816.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:hin:complx:2503816","is_oa":false,"landing_page_url":"http://downloads.hindawi.com/journals/8503/2018/2503816.xml","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"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":"article"},{"id":"pmh:oai:doaj.org/article:a851eef1ba7542c680f0e9eb1caa72f9","is_oa":true,"landing_page_url":"https://doaj.org/article/a851eef1ba7542c680f0e9eb1caa72f9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Complexity, Vol 2018 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2018/2503816","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2018/2503816","pdf_url":"http://downloads.hindawi.com/journals/complexity/2018/2503816.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6600000262260437}],"awards":[{"id":"https://openalex.org/G3701971603","display_name":null,"funder_award_id":"16YJCZH076","funder_id":"https://openalex.org/F4320321106","funder_display_name":"Ministry of Education of the People's Republic of China"},{"id":"https://openalex.org/G5032382152","display_name":null,"funder_award_id":"2018KF01","funder_id":"https://openalex.org/F4320321470","funder_display_name":"Beijing University of Posts and Telecommunications"},{"id":"https://openalex.org/G5837478851","display_name":null,"funder_award_id":"2018KF01","funder_id":"https://openalex.org/F4320321106","funder_display_name":"Ministry of Education of the People's Republic of China"},{"id":"https://openalex.org/G5859881043","display_name":null,"funder_award_id":"61672553","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6520305882","display_name":null,"funder_award_id":"16YJCZH076","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"},{"id":"https://openalex.org/F4320321106","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934"},{"id":"https://openalex.org/F4320321470","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59"},{"id":"https://openalex.org/F4320335800","display_name":"Key Laboratory of Trustworthy Distributed Computing and Service of Ministry of Education","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2803895891.pdf","grobid_xml":"https://content.openalex.org/works/W2803895891.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W244856213","https://openalex.org/W1536737962","https://openalex.org/W1880262756","https://openalex.org/W1960685374","https://openalex.org/W1969486090","https://openalex.org/W1991860612","https://openalex.org/W2000411838","https://openalex.org/W2017921654","https://openalex.org/W2048978851","https://openalex.org/W2055400882","https://openalex.org/W2063904635","https://openalex.org/W2076219102","https://openalex.org/W2134731454","https://openalex.org/W2137958601","https://openalex.org/W2142920810","https://openalex.org/W2147152072","https://openalex.org/W2161443453","https://openalex.org/W2168332560","https://openalex.org/W2169821025","https://openalex.org/W2329099884","https://openalex.org/W2330325623","https://openalex.org/W2437541582","https://openalex.org/W2552464009","https://openalex.org/W2561032512","https://openalex.org/W2629386751","https://openalex.org/W2743763476","https://openalex.org/W2755644830","https://openalex.org/W3003555171","https://openalex.org/W3122775348","https://openalex.org/W4233135949","https://openalex.org/W4237791300","https://openalex.org/W6681698864"],"related_works":["https://openalex.org/W2047050287","https://openalex.org/W2888805565","https://openalex.org/W4312773271","https://openalex.org/W4315588616","https://openalex.org/W2494246486","https://openalex.org/W2769501189","https://openalex.org/W2962686197","https://openalex.org/W2207653751","https://openalex.org/W4293863151","https://openalex.org/W2122605835"],"abstract_inverted_index":{"In":[0,94,134],"the":[1,13,44,126,130,151],"present":[2],"big":[3,16,48],"data":[4,17,59,112,163,205],"background,":[5],"how":[6],"to":[7,27,62,85,104,110,174,187],"effectively":[8,197],"excavate":[9],"useful":[10],"information":[11],"is":[12,18,26,65,168,185],"problem":[14],"that":[15,148,208,222],"facing":[19],"now.":[20],"The":[21,162],"purpose":[22],"of":[23,33,37,46,56,69,89,123,128,154,165],"this":[24,135],"study":[25],"construct":[28],"a":[29,40,53,77,86,121,144,202],"more":[30,96],"effective":[31,67,97],"method":[32,68],"mining":[34,129,189,215],"interest":[35,132],"preferences":[36],"users":[38],"in":[39,43,81,92,176,201,214,228],"particular":[41],"field":[42],"context":[45],"today\u2019s":[47,95],"data.":[49],"We":[50],"mainly":[51],"use":[52],"large":[54,87],"number":[55,88],"user":[57,216],"text":[58,70,181,184],"from":[60],"microblog":[61,155,204],"study.":[63],"LDA":[64,83],"an":[66],"mining,":[71],"but":[72],"it":[73],"will":[74],"not":[75],"play":[76],"very":[78],"good":[79,226],"role":[80],"applying":[82],"directly":[84],"short":[90,101,116,156,166,178,195],"texts":[91,102,109,117,157,160,167,173,193,196],"microblog.":[93],"topic":[98,146],"modeling":[99],"project,":[100],"need":[103],"be":[105],"aggregated":[106,115],"into":[107],"long":[108,159,172,183,192],"avoid":[111],"sparsity.":[113],"However,":[114],"are":[118],"mixed":[119],"with":[120],"lot":[122],"noise,":[124],"reducing":[125],"accuracy":[127],"user\u2019s":[131],"preferences.":[133],"paper,":[136],"we":[137,219],"propose":[138],"Combining":[139],"Latent":[140],"Dirichlet":[141],"Allocation":[142],"(CLDA),":[143],"new":[145],"model":[147],"can":[149],"learn":[150],"potential":[152],"topics":[153],"and":[158,194,218],"simultaneously.":[161],"sparsity":[164],"avoided":[169],"by":[170],"aggregating":[171],"assist":[175],"learning":[177],"texts.":[179],"Short":[180],"filtering":[182],"reused":[186],"improve":[188],"accuracy,":[190],"making":[191],"combined.":[198],"Experimental":[199],"results":[200],"real":[203],"set":[206],"show":[207],"CLDA":[209,223],"outperforms":[210],"many":[211],"advanced":[212],"models":[213],"interest,":[217],"also":[220,224],"confirm":[221],"has":[225],"performance":[227],"recommending":[229],"systems.":[230]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}