{"id":"https://openalex.org/W2798523152","doi":"https://doi.org/10.1145/3184558.3191629","title":"LDA Meets Word2Vec","display_name":"LDA Meets Word2Vec","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2798523152","doi":"https://doi.org/10.1145/3184558.3191629","mag":"2798523152"},"language":"en","primary_location":{"id":"doi:10.1145/3184558.3191629","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3184558.3191629","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3184558.3191629","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012413411","display_name":"Changzhou Li","orcid":"https://orcid.org/0000-0002-0848-2062"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changzhou Li","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079921526","display_name":"Junyu Guo","orcid":"https://orcid.org/0000-0001-9462-9501"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junyu Guo","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102027564","display_name":"Yao Lu","orcid":"https://orcid.org/0000-0001-9004-9569"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Lu","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012043765","display_name":"Junfeng Wu","orcid":"https://orcid.org/0000-0003-1263-3051"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junfeng Wu","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046099997","display_name":"Yongrui Zhang","orcid":"https://orcid.org/0000-0003-1066-7442"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongrui Zhang","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034402567","display_name":"Zhongzhou Xia","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongzhou Xia","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112360220","display_name":"Tianchen Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianchen Wang","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100544742","display_name":"Dantian Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dantian Yu","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010984528","display_name":"Xurui Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xurui Chen","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085472864","display_name":"Peidong Liu","orcid":"https://orcid.org/0000-0002-9767-6220"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peidong Liu","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":39,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1699","last_page":"1706"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9987000226974487,"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":0.9987000226974487,"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":0.9976999759674072,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9973999857902527,"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/cluster-analysis","display_name":"Cluster analysis","score":0.8750754594802856},{"id":"https://openalex.org/keywords/word2vec","display_name":"Word2vec","score":0.8596386909484863},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7903717756271362},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6359588503837585},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.5563011765480042},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5246663093566895},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.5001473426818848},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4588518738746643},{"id":"https://openalex.org/keywords/document-clustering","display_name":"Document clustering","score":0.45064881443977356},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.42260655760765076},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39120832085609436},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3586145043373108},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35249364376068115},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1290716826915741}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8750754594802856},{"id":"https://openalex.org/C2776461190","wikidata":"https://www.wikidata.org/wiki/Q22673982","display_name":"Word2vec","level":3,"score":0.8596386909484863},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7903717756271362},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6359588503837585},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.5563011765480042},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5246663093566895},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.5001473426818848},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4588518738746643},{"id":"https://openalex.org/C177937566","wikidata":"https://www.wikidata.org/wiki/Q4223102","display_name":"Document clustering","level":3,"score":0.45064881443977356},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.42260655760765076},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39120832085609436},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3586145043373108},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35249364376068115},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1290716826915741},{"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/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3184558.3191629","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3184558.3191629","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3184558.3191629","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3184558.3191629","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8100000023841858,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W81280874","https://openalex.org/W198476337","https://openalex.org/W1614298861","https://openalex.org/W1631405315","https://openalex.org/W1765927794","https://openalex.org/W1880262756","https://openalex.org/W2031976076","https://openalex.org/W2087246227","https://openalex.org/W2095980495","https://openalex.org/W2097057650","https://openalex.org/W2130681206","https://openalex.org/W2164139207","https://openalex.org/W2171836785","https://openalex.org/W2251410829","https://openalex.org/W2334209830","https://openalex.org/W2429335739","https://openalex.org/W2594674086","https://openalex.org/W2768113420","https://openalex.org/W2950577311","https://openalex.org/W6639619044"],"related_works":["https://openalex.org/W2905749112","https://openalex.org/W1997182898","https://openalex.org/W2346530426","https://openalex.org/W3099354896","https://openalex.org/W2890749918","https://openalex.org/W4287599800","https://openalex.org/W2772765860","https://openalex.org/W4312264180","https://openalex.org/W2594674086","https://openalex.org/W4309228610"],"abstract_inverted_index":{"Clustering":[0],"narrow-domain":[1],"short":[2,15],"texts,":[3],"such":[4],"as":[5],"academic":[6],"abstracts,":[7],"is":[8,56,86],"an":[9,101],"extremely":[10],"difficult":[11],"clustering":[12,26,69,81,182,193],"problem.":[13],"Firstly,":[14],"texts":[16],"lead":[17],"to":[18,36,46,60,73,91,118,125,138,172],"low":[19],"frequency":[20],"and":[21,30,42,143,145,179,201],"sparseness":[22],"of":[23,39,100,109,154,170,195],"words,":[24],"making":[25],"results":[27,153,183,189,194],"highly":[28],"unstable":[29],"inaccurate;":[31],"Secondly,":[32],"narrow":[33],"domain":[34],"leads":[35],"great":[37],"overlapping":[38],"insignificant":[40],"words":[41,131],"makes":[43],"it":[44],"hard":[45],"distinguish":[47],"between":[48],"sub-domains,":[49],"or":[50],"fine-grained":[51],"clusters.":[52],"The":[53],"vocabulary":[54],"size":[55],"also":[57],"too":[58],"small":[59],"construct":[61],"a":[62,75,115,140],"good":[63],"word":[64],"bag":[65],"needed":[66],"by":[67,185],"traditional":[68],"algorithms":[70],"like":[71],"LDA":[72,144],"give":[74],"meaningful":[76],"topic":[77,108],"distribution.":[78],"A":[79],"novel":[80,116],"model,":[82],"Partitioned":[83],"Word2Vec-LDA":[84],"(PW-LDA),":[85],"proposed":[87],"in":[88],"this":[89],"paper":[90],"tackle":[92],"the":[93,97,107,110,122,152,160,192],"described":[94],"problems.":[95],"Since":[96],"purpose":[98,136],"sentences":[99,137],"abstract":[102,167],"contain":[103],"crucial":[104],"information":[105],"about":[106],"paper,":[111],"we":[112,157],"firstly":[113],"implement":[114],"algorithm":[117],"extract":[119],"them":[120],"from":[121,134],"abstracts":[123,161],"according":[124],"its":[126],"structural":[127],"features.":[128],"Then":[129],"high-frequency":[130],"are":[132,148,197],"removed":[133],"those":[135],"get":[139],"purified-purpose":[141],"corpus":[142],"Word2Vec":[146],"models":[147],"trained.":[149],"After":[150],"combining":[151],"both":[155],"models,":[156],"can":[158],"cluster":[159,173],"more":[162,199],"precisely.":[163],"Our":[164],"model":[165],"uses":[166],"text":[168],"instead":[169],"keywords":[171,175],"because":[174],"may":[176],"be":[177],"ambiguous":[178],"cause":[180],"unsatisfied":[181],"shown":[184],"previous":[186],"work.":[187],"Experimental":[188],"show":[190],"that":[191],"PW-LDA":[196],"much":[198],"accurate":[200],"stable":[202],"than":[203],"state-of-the-art":[204],"techniques.":[205]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":6}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2018-05-07T00:00:00"}
