{"id":"https://openalex.org/W2129350855","doi":"https://doi.org/10.1109/iscslp.2010.5684906","title":"Topic-weak-correlated Latent Dirichlet allocation","display_name":"Topic-weak-correlated Latent Dirichlet allocation","publication_year":2010,"publication_date":"2010-11-01","ids":{"openalex":"https://openalex.org/W2129350855","doi":"https://doi.org/10.1109/iscslp.2010.5684906","mag":"2129350855"},"language":"en","primary_location":{"id":"doi:10.1109/iscslp.2010.5684906","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscslp.2010.5684906","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 7th International Symposium on Chinese Spoken Language Processing","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/A5112591599","display_name":"Yimin Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yimin Tan","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China","Department of Electronic Engineering, Tsinghua University, Beijing, CHINA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, CHINA#TAB#","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010173604","display_name":"Zhijian Ou","orcid":"https://orcid.org/0000-0002-9018-5074"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhijian Ou","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China","Department of Electronic Engineering, Tsinghua University, Beijing, CHINA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, CHINA#TAB#","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.23157502,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"224","last_page":"228"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10028","display_name":"Topic Modeling","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9994000196456909,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.996399998664856,"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/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.9877908229827881},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.8741016983985901},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7095885872840881},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6788228154182434},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6291201710700989},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.599200963973999},{"id":"https://openalex.org/keywords/latent-semantic-analysis","display_name":"Latent semantic analysis","score":0.5111032128334045},{"id":"https://openalex.org/keywords/dirichlet-distribution","display_name":"Dirichlet distribution","score":0.4729183316230774},{"id":"https://openalex.org/keywords/meaning","display_name":"Meaning (existential)","score":0.4566974937915802},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.24349606037139893},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19301944971084595},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.06079182028770447}],"concepts":[{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.9877908229827881},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.8741016983985901},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7095885872840881},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6788228154182434},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6291201710700989},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.599200963973999},{"id":"https://openalex.org/C170133592","wikidata":"https://www.wikidata.org/wiki/Q1806883","display_name":"Latent semantic analysis","level":2,"score":0.5111032128334045},{"id":"https://openalex.org/C169214877","wikidata":"https://www.wikidata.org/wiki/Q981016","display_name":"Dirichlet distribution","level":3,"score":0.4729183316230774},{"id":"https://openalex.org/C2780876879","wikidata":"https://www.wikidata.org/wiki/Q3054749","display_name":"Meaning (existential)","level":2,"score":0.4566974937915802},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.24349606037139893},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19301944971084595},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.06079182028770447},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C182310444","wikidata":"https://www.wikidata.org/wiki/Q1332643","display_name":"Boundary value problem","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iscslp.2010.5684906","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscslp.2010.5684906","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 7th International Symposium on Chinese Spoken Language Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.415.5346","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.415.5346","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://pages.cs.wisc.edu/~yimin/TWC-LDA.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W153090119","https://openalex.org/W1576520375","https://openalex.org/W1581986412","https://openalex.org/W1880262756","https://openalex.org/W2096610504","https://openalex.org/W2103587173","https://openalex.org/W2107034620","https://openalex.org/W2128925311","https://openalex.org/W2132827946","https://openalex.org/W3099640513","https://openalex.org/W6606271780","https://openalex.org/W6634442568","https://openalex.org/W6634664379"],"related_works":["https://openalex.org/W2888805565","https://openalex.org/W2497860580","https://openalex.org/W2995939990","https://openalex.org/W2914864478","https://openalex.org/W2891616219","https://openalex.org/W3204672119","https://openalex.org/W2402771052","https://openalex.org/W2474958513","https://openalex.org/W2049446342","https://openalex.org/W2970965181"],"abstract_inverted_index":{"Latent":[0],"Dirichlet":[1],"allocation":[2],"(LDA)":[3],"has":[4],"been":[5],"widely":[6],"used":[7],"for":[8,22,92],"analyzing":[9],"large":[10],"text":[11],"corpora.":[12],"In":[13],"this":[14],"paper":[15],"we":[16],"propose":[17],"the":[18,42,46,49,53,59,83,86,89],"topic-weak-correlated":[19],"LDA":[20,91],"(TWC-LDA)":[21],"topic":[23,63,95],"modeling,":[24],"which":[25],"constrains":[26],"different":[27],"topics":[28,55],"to":[29,69],"be":[30,66],"weak-correlated.":[31],"This":[32],"is":[33],"technically":[34],"achieved":[35],"by":[36],"placing":[37],"a":[38,70],"special":[39],"prior":[40],"over":[41,88],"topic-word":[43,50],"distributions.":[44],"Reducing":[45],"overlapping":[47],"between":[48],"distributions":[51],"makes":[52],"learned":[54],"more":[56],"interpretable":[57],"in":[58],"sense":[60],"that":[61],"each":[62],"word-distribution":[64],"can":[65],"clearly":[67],"associated":[68],"distinctive":[71],"semantic":[72],"meaning.":[73],"Experimental":[74],"results":[75],"on":[76],"both":[77],"synthetic":[78],"and":[79,97],"real-world":[80],"corpus":[81],"show":[82],"superiority":[84],"of":[85],"TWC-LDA":[87],"basic":[90],"semantically":[93],"meaningful":[94],"discovery":[96],"document":[98],"classification.":[99]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-10T00:00:00"}