{"id":"https://openalex.org/W3011595896","doi":"https://doi.org/10.1145/3376927","title":"An Enhanced Neural Network Approach to Person-Job Fit in Talent Recruitment","display_name":"An Enhanced Neural Network Approach to Person-Job Fit in Talent Recruitment","publication_year":2020,"publication_date":"2020-02-11","ids":{"openalex":"https://openalex.org/W3011595896","doi":"https://doi.org/10.1145/3376927","mag":"3011595896"},"language":"en","primary_location":{"id":"doi:10.1145/3376927","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3376927","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/A5102883290","display_name":"Chuan Qin","orcid":"https://orcid.org/0000-0002-5354-8630"},"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":true,"raw_author_name":"Chuan Qin","raw_affiliation_strings":["School of Computer Science, University of Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]},{"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"],"affiliations":[{"raw_affiliation_string":"Baidu Talent Intelligence Center, Baidu Inc","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"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100768322","display_name":"Chen Zhu","orcid":null},"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":"Chen Zhu","raw_affiliation_strings":["Baidu Talent Intelligence Center, Baidu Inc"],"affiliations":[{"raw_affiliation_string":"Baidu Talent Intelligence Center, Baidu Inc","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023893507","display_name":"Chao Ma","orcid":"https://orcid.org/0000-0002-7443-6267"},"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":"Chao Ma","raw_affiliation_strings":["Baidu Talent Intelligence Center, Baidu Inc"],"affiliations":[{"raw_affiliation_string":"Baidu Talent Intelligence Center, Baidu Inc","institution_ids":["https://openalex.org/I98301712"]}]},{"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"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Science and Technology of 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/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":"Hui Xiong","raw_affiliation_strings":["School of Computer Science, University of Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5102883290"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":17.0818,"has_fulltext":false,"cited_by_count":106,"citation_normalized_percentile":{"value":0.9914106,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"38","issue":"2","first_page":"1","last_page":"33"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9979000091552734,"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":0.9979000091552734,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9979000091552734,"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/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"}}],"keywords":[{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.8350427150726318},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6903666257858276},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.6431844234466553},{"id":"https://openalex.org/keywords/job-analysis","display_name":"Job analysis","score":0.6019679307937622},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5734444260597229},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.47449231147766113},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44238901138305664},{"id":"https://openalex.org/keywords/job-design","display_name":"Job design","score":0.43664246797561646},{"id":"https://openalex.org/keywords/job-performance","display_name":"Job performance","score":0.42235106229782104},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3759492039680481},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.32264643907546997},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.32047855854034424},{"id":"https://openalex.org/keywords/job-satisfaction","display_name":"Job satisfaction","score":0.17967599630355835},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.11553609371185303},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.11462318897247314}],"concepts":[{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.8350427150726318},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6903666257858276},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6431844234466553},{"id":"https://openalex.org/C58346731","wikidata":"https://www.wikidata.org/wiki/Q627339","display_name":"Job analysis","level":3,"score":0.6019679307937622},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5734444260597229},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.47449231147766113},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44238901138305664},{"id":"https://openalex.org/C139140526","wikidata":"https://www.wikidata.org/wiki/Q8034614","display_name":"Job design","level":4,"score":0.43664246797561646},{"id":"https://openalex.org/C174954385","wikidata":"https://www.wikidata.org/wiki/Q6206740","display_name":"Job performance","level":3,"score":0.42235106229782104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3759492039680481},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.32264643907546997},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.32047855854034424},{"id":"https://openalex.org/C2718322","wikidata":"https://www.wikidata.org/wiki/Q629463","display_name":"Job satisfaction","level":2,"score":0.17967599630355835},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.11553609371185303},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.11462318897247314},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3376927","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3376927","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":[{"display_name":"Decent work and economic growth","score":0.7300000190734863,"id":"https://metadata.un.org/sdg/8"}],"awards":[{"id":"https://openalex.org/G5071813862","display_name":null,"funder_award_id":"91746301, 61703386, 61836013, and U1605251","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":76,"referenced_works":["https://openalex.org/W1509466891","https://openalex.org/W1966443646","https://openalex.org/W1979411553","https://openalex.org/W1994092846","https://openalex.org/W2002349151","https://openalex.org/W2005646316","https://openalex.org/W2024018222","https://openalex.org/W2024082504","https://openalex.org/W2048239613","https://openalex.org/W2051639611","https://openalex.org/W2061873838","https://openalex.org/W2064675550","https://openalex.org/W2079735306","https://openalex.org/W2119336203","https://openalex.org/W2120615054","https://openalex.org/W2124187902","https://openalex.org/W2128424290","https://openalex.org/W2136189984","https://openalex.org/W2140036815","https://openalex.org/W2171313960","https://openalex.org/W2186845332","https://openalex.org/W2246827810","https://openalex.org/W2250966211","https://openalex.org/W2296283641","https://openalex.org/W2319358180","https://openalex.org/W2335082123","https://openalex.org/W2510940142","https://openalex.org/W2512706923","https://openalex.org/W2514580099","https://openalex.org/W2514768994","https://openalex.org/W2516369484","https://openalex.org/W2556605533","https://openalex.org/W2573426660","https://openalex.org/W2582558662","https://openalex.org/W2592622430","https://openalex.org/W2604738573","https://openalex.org/W2605350416","https://openalex.org/W2622365670","https://openalex.org/W2738486593","https://openalex.org/W2739273093","https://openalex.org/W2740130602","https://openalex.org/W2743064457","https://openalex.org/W2771472444","https://openalex.org/W2773879121","https://openalex.org/W2788667846","https://openalex.org/W2788893025","https://openalex.org/W2791779647","https://openalex.org/W2798507773","https://openalex.org/W2798868970","https://openalex.org/W2798908418","https://openalex.org/W2806440576","https://openalex.org/W2808631100","https://openalex.org/W2892181857","https://openalex.org/W2893564970","https://openalex.org/W2896140001","https://openalex.org/W2897660518","https://openalex.org/W2904064004","https://openalex.org/W2907122279","https://openalex.org/W2908559915","https://openalex.org/W2912404939","https://openalex.org/W2913189099","https://openalex.org/W2913668833","https://openalex.org/W2950493386","https://openalex.org/W2952718163","https://openalex.org/W2954698196","https://openalex.org/W2965464754","https://openalex.org/W2983965928","https://openalex.org/W2987222756","https://openalex.org/W2991522931","https://openalex.org/W3004083821","https://openalex.org/W3098931577","https://openalex.org/W3100612294","https://openalex.org/W3106302634","https://openalex.org/W3122507327","https://openalex.org/W4288083766","https://openalex.org/W6607262404"],"related_works":["https://openalex.org/W3046190687","https://openalex.org/W2516348321","https://openalex.org/W2565907132","https://openalex.org/W2241466599","https://openalex.org/W132413899","https://openalex.org/W2784897851","https://openalex.org/W2112368856","https://openalex.org/W2621302723","https://openalex.org/W1485557866","https://openalex.org/W2056393188"],"abstract_inverted_index":{"The":[0,132],"widespread":[1],"use":[2],"of":[3,66,82,116,185,198,249,262,280],"online":[4],"recruitment":[5,221],"services":[6],"has":[7,113],"led":[8],"to":[9,22,38,136,180,202,227],"an":[10],"information":[11,140],"explosion":[12],"in":[13,88,142,237,246],"the":[14,31,35,39,51,63,76,118,129,138,182,195,247,260,276,281],"job":[15,58,145,157,160,186,200,243,250],"market.":[16],"As":[17],"a":[18,93,114,151,203,211,252,270],"result,":[19],"recruiters":[20],"have":[21],"seek":[23],"intelligent":[24],"ways":[25],"for":[26,33,155,188,214,232,258],"Person-Job":[27,45,215],"Fit,":[28],"which":[29,70,112],"is":[30,135,256],"bridge":[32],"adapting":[34],"right":[36,40],"candidates":[37],"positions.":[41],"Existing":[42],"studies":[43],"on":[44,49,62,120,164,219,269],"Fit":[46,216],"usually":[47],"focus":[48],"measuring":[50],"matching":[52],"degree":[53],"between":[54],"talent":[55,238,240],"qualification":[56],"and":[57,79,123,159,242,278,283],"requirements":[59,158,187],"mainly":[60],"based":[61,163,218],"manual":[64,121],"inspection":[65],"human":[67,83],"resource":[68],"experts,":[69],"could":[71],"be":[72],"easily":[73],"misguided":[74],"by":[75],"subjective,":[77],"incomplete,":[78],"inefficient":[80],"nature":[81],"judgment.":[84],"To":[85],"that":[86],"end,":[87],"this":[89,170],"article,":[90],"we":[91,149,209,224],"propose":[92,150],"novel":[94,253],"end-to-end":[95],"T":[96],"opic-based":[97],"A":[98],"bility-aware":[99],"P":[100],"erson-":[101],"J":[102],"ob":[103],"F":[104],"it":[105],"N":[106,108],"eural":[107],"etwork":[109],"(TAPJFNN)":[110],"framework,":[111],"goal":[115],"reducing":[117],"dependence":[119],"labor":[122],"can":[124],"provide":[125],"better":[126],"interpretability":[127,279],"about":[128],"fitting":[130],"results.":[131],"key":[133],"idea":[134],"exploit":[137,228],"rich":[139],"available":[141],"abundant":[143],"historical":[144,220],"application":[146,248],"data.":[147],"Specifically,":[148],"word-level":[152],"semantic":[153,189],"representation":[154],"both":[156],"seekers\u2019":[161],"experiences":[162],"Recurrent":[165],"Neural":[166],"Network":[167],"(RNN).":[168],"Along":[169],"line,":[171],"two":[172,234],"hierarchical":[173],"topic-based":[174],"ability-aware":[175],"attention":[176],"strategies":[177],"are":[178],"designed":[179,257],"measure":[181,194],"different":[183,196],"importance":[184],"representation,":[190],"as":[191,193],"well":[192],"contribution":[197],"each":[199],"experience":[201],"specific":[204,235],"ability":[205],"requirement.":[206],"In":[207],"addition,":[208],"design":[210],"refinement":[212],"strategy":[213],"prediction":[217],"records.":[222],"Furthermore,":[223],"introduce":[225],"how":[226],"our":[229],"TAPJFNN":[230,282],"framework":[231],"enabling":[233],"applications":[236],"recruitment:":[239],"sourcing":[241],"recommendation.":[244],"Particularly,":[245],"recommendation,":[251],"training":[254],"mechanism":[255],"addressing":[259],"challenge":[261],"biased":[263],"negative":[264],"labels.":[265],"Finally,":[266],"extensive":[267],"experiments":[268],"large-scale":[271],"real-world":[272],"dataset":[273],"clearly":[274],"validate":[275],"effectiveness":[277],"its":[284],"variants":[285],"compared":[286],"with":[287],"several":[288],"baselines.":[289]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":21},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":30},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}