{"id":"https://openalex.org/W3198193660","doi":"https://doi.org/10.1145/3469654","title":"Joint Representation Learning with Relation-Enhanced Topic Models for Intelligent Job Interview Assessment","display_name":"Joint Representation Learning with Relation-Enhanced Topic Models for Intelligent Job Interview Assessment","publication_year":2021,"publication_date":"2021-09-08","ids":{"openalex":"https://openalex.org/W3198193660","doi":"https://doi.org/10.1145/3469654","mag":"3198193660"},"language":"en","primary_location":{"id":"doi:10.1145/3469654","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469654","pdf_url":null,"source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","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/A5075007087","display_name":"Dazhong Shen","orcid":"https://orcid.org/0000-0002-3947-4153"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dazhong Shen","raw_affiliation_strings":["School of Computer Science, University of Science and Technology of China, Hefei, Anhui, China"],"raw_orcid":"https://orcid.org/0000-0002-3947-4153","affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Science and Technology of China, Hefei, Anhui, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102883290","display_name":"Chuan Qin","orcid":"https://orcid.org/0000-0002-5354-8630"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuan Qin","raw_affiliation_strings":["Baidu Talent Intelligence Center, Baidu Inc., Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5354-8630","affiliations":[{"raw_affiliation_string":"Baidu Talent Intelligence Center, Baidu Inc., Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049015446","display_name":"Hengshu Zhu","orcid":"https://orcid.org/0000-0003-4570-643X"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengshu Zhu","raw_affiliation_strings":["Baidu Talent Intelligence Center, Baidu Inc., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Talent Intelligence Center, Baidu Inc., Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025292786","display_name":"Tong Xu","orcid":"https://orcid.org/0000-0003-4246-5386"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Xu","raw_affiliation_strings":["School of Computer Science, University of Science and Technology of China, Hefei, Anhui, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Science and Technology of China, Hefei, Anhui, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048237545","display_name":"Enhong Chen","orcid":"https://orcid.org/0000-0002-4835-4102"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Enhong Chen","raw_affiliation_strings":["School of Computer Science, University of Science and Technology of China, Hefei, Anhui, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Science and Technology of China, Hefei, Anhui, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101862104","display_name":"Hui Xiong","orcid":"https://orcid.org/0000-0001-6016-6465"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hui Xiong","raw_affiliation_strings":["Rutgers, the State University of New Jersey, Newark, NJ, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers, the State University of New Jersey, Newark, NJ, United States","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7743,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.87419203,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"40","issue":"1","first_page":"1","last_page":"36"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9948999881744385,"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":0.9948999881744385,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9922000169754028,"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"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9907000064849854,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7341643571853638},{"id":"https://openalex.org/keywords/job-interview","display_name":"Job interview","score":0.7253825068473816},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5170555710792542},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4842383563518524},{"id":"https://openalex.org/keywords/telephone-interview","display_name":"Telephone interview","score":0.4451262354850769},{"id":"https://openalex.org/keywords/interview","display_name":"Interview","score":0.4418790340423584},{"id":"https://openalex.org/keywords/job-analysis","display_name":"Job analysis","score":0.4381105899810791},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.43106091022491455},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4130736291408539},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41065728664398193},{"id":"https://openalex.org/keywords/applied-psychology","display_name":"Applied psychology","score":0.3436875641345978},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.24438151717185974},{"id":"https://openalex.org/keywords/job-satisfaction","display_name":"Job satisfaction","score":0.22984400391578674},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.1513386368751526}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7341643571853638},{"id":"https://openalex.org/C2776587543","wikidata":"https://www.wikidata.org/wiki/Q850171","display_name":"Job interview","level":2,"score":0.7253825068473816},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5170555710792542},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4842383563518524},{"id":"https://openalex.org/C2778834376","wikidata":"https://www.wikidata.org/wiki/Q7696504","display_name":"Telephone interview","level":2,"score":0.4451262354850769},{"id":"https://openalex.org/C24845683","wikidata":"https://www.wikidata.org/wiki/Q178651","display_name":"Interview","level":2,"score":0.4418790340423584},{"id":"https://openalex.org/C58346731","wikidata":"https://www.wikidata.org/wiki/Q627339","display_name":"Job analysis","level":3,"score":0.4381105899810791},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.43106091022491455},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4130736291408539},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41065728664398193},{"id":"https://openalex.org/C75630572","wikidata":"https://www.wikidata.org/wiki/Q538904","display_name":"Applied psychology","level":1,"score":0.3436875641345978},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.24438151717185974},{"id":"https://openalex.org/C2718322","wikidata":"https://www.wikidata.org/wiki/Q629463","display_name":"Job satisfaction","level":2,"score":0.22984400391578674},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.1513386368751526},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3469654","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469654","pdf_url":null,"source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.4399999976158142,"display_name":"Decent work and economic growth"}],"awards":[{"id":"https://openalex.org/G4417038889","display_name":null,"funder_award_id":"91746301, 71531001, 61836013, U20A20229, and 62072423","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":70,"referenced_works":["https://openalex.org/W178169250","https://openalex.org/W1509466891","https://openalex.org/W1516111018","https://openalex.org/W1831028724","https://openalex.org/W1955368298","https://openalex.org/W1979411553","https://openalex.org/W2003996632","https://openalex.org/W2004647285","https://openalex.org/W2024018222","https://openalex.org/W2033593667","https://openalex.org/W2051639611","https://openalex.org/W2064675550","https://openalex.org/W2066365352","https://openalex.org/W2072644219","https://openalex.org/W2105621451","https://openalex.org/W2115979064","https://openalex.org/W2128424290","https://openalex.org/W2135790056","https://openalex.org/W2171343266","https://openalex.org/W2172085063","https://openalex.org/W2225156818","https://openalex.org/W2483593449","https://openalex.org/W2507934469","https://openalex.org/W2512706923","https://openalex.org/W2514580099","https://openalex.org/W2514768994","https://openalex.org/W2531037333","https://openalex.org/W2554210178","https://openalex.org/W2602753196","https://openalex.org/W2604738573","https://openalex.org/W2736274677","https://openalex.org/W2743064457","https://openalex.org/W2745475103","https://openalex.org/W2792805964","https://openalex.org/W2795478131","https://openalex.org/W2798507773","https://openalex.org/W2808631100","https://openalex.org/W2891585127","https://openalex.org/W2893564970","https://openalex.org/W2900464008","https://openalex.org/W2900806287","https://openalex.org/W2904064004","https://openalex.org/W2904614016","https://openalex.org/W2911495555","https://openalex.org/W2912172494","https://openalex.org/W2912500072","https://openalex.org/W2913668833","https://openalex.org/W2949169239","https://openalex.org/W2951738332","https://openalex.org/W2952264928","https://openalex.org/W2952718163","https://openalex.org/W2962994101","https://openalex.org/W2969519670","https://openalex.org/W2971133212","https://openalex.org/W3011595896","https://openalex.org/W3012912574","https://openalex.org/W3034873720","https://openalex.org/W3035511822","https://openalex.org/W3098931577","https://openalex.org/W3100612294","https://openalex.org/W3101380508","https://openalex.org/W3102331315","https://openalex.org/W3149252920","https://openalex.org/W3167367835","https://openalex.org/W3172303411","https://openalex.org/W3187993652","https://openalex.org/W3196728560","https://openalex.org/W4213069590","https://openalex.org/W6641262548","https://openalex.org/W7052871438"],"related_works":["https://openalex.org/W4389009387","https://openalex.org/W3082302788","https://openalex.org/W2073300957","https://openalex.org/W2941248034","https://openalex.org/W3088612703","https://openalex.org/W1965360190","https://openalex.org/W2156546954","https://openalex.org/W1669428460","https://openalex.org/W4388936879","https://openalex.org/W284377592"],"abstract_inverted_index":{"The":[0],"job":[1,41,77,106,180,186,231,239],"interview":[2,42,52,62,78,84,111,165,181,187,208,240],"is":[3,45],"considered":[4],"as":[5],"one":[6],"of":[7,59,159,178,220,238],"the":[8,25,29,40,56,60,81,103,124,150,157,160,175,184,218],"most":[9],"essential":[10],"tasks":[11],"in":[12,23,67,189,230],"talent":[13],"recruitment,":[14],"which":[15,223],"forms":[16],"a":[17,90,168],"bridge":[18],"between":[19],"candidates":[20],"and":[21,110,155,204,233],"employers":[22],"fitting":[24],"right":[26,30],"person":[27],"for":[28,145,197,207],"job.":[31],"While":[32],"substantial":[33],"efforts":[34],"have":[35,48],"been":[36],"made":[37],"on":[38,97,213],"improving":[39],"process,":[43],"it":[44],"inevitable":[46],"to":[47,55,75,101,122,135,226],"biased":[49],"or":[50],"inconsistent":[51],"assessment":[53],"due":[54],"subjective":[57],"nature":[58],"traditional":[61],"process.":[63],"To":[64],"this":[65,68],"end,":[66],"article,":[69],"we":[70,87,114,133,193],"propose":[71,134],"three":[72],"novel":[73],"approaches":[74,171,196],"intelligent":[76],"by":[79,127,141],"learning":[80],"large-scale":[82],"real-world":[83,199,214],"data.":[85],"Specifically,":[86],"first":[88],"develop":[89],"preliminary":[91],"model,":[92,119],"named":[93,120],"Joint":[94],"Learning":[95],"Model":[96],"Interview":[98],"Assessment":[99],"(JLMIA),":[100],"mine":[102],"relationship":[104],"among":[105],"description,":[107],"candidate":[108],"resume,":[109],"assessment.":[112,209,241],"Then,":[113],"further":[115],"design":[116],"an":[117,235],"enhanced":[118],"Neural-JLMIA,":[121],"improve":[123],"representative":[125,176],"capability":[126],"applying":[128],"neural":[129],"variance":[130],"inference.":[131],"Last,":[132],"refine":[136],"JLMIA":[137],"with":[138],"Refined-JLMIA":[139],"(R-JLMIA)":[140],"modeling":[142],"individual":[143],"characteristics":[144],"each":[146],"collection,":[147],"i.e.,":[148,201],"disentangling":[149],"core":[151],"competences":[152],"from":[153,183],"resume":[154],"capturing":[156],"evolution":[158],"semantic":[161],"topics":[162],"over":[163],"different":[164,179],"rounds.":[166],"As":[167],"result,":[169],"our":[170,195,221],"can":[172,224],"effectively":[173],"learn":[174],"perspectives":[177],"processes":[182],"successful":[185],"records":[188],"history.":[190],"In":[191],"addition,":[192],"exploit":[194],"two":[198],"applications,":[200],"person-job":[202],"fit":[203],"skill":[205],"recommendation":[206],"Extensive":[210],"experiments":[211],"conducted":[212],"data":[215],"clearly":[216],"validate":[217],"effectiveness":[219],"models,":[222],"lead":[225],"substantially":[227],"less":[228],"bias":[229],"interviews":[232],"provide":[234],"interpretable":[236],"understanding":[237]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
