{"id":"https://openalex.org/W4402198744","doi":"https://doi.org/10.3233/idt-240670","title":"Hybrid convolutional neural networks in human resource recommendation","display_name":"Hybrid convolutional neural networks in human resource recommendation","publication_year":2024,"publication_date":"2024-09-03","ids":{"openalex":"https://openalex.org/W4402198744","doi":"https://doi.org/10.3233/idt-240670"},"language":"en","primary_location":{"id":"doi:10.3233/idt-240670","is_oa":false,"landing_page_url":"https://doi.org/10.3233/idt-240670","pdf_url":null,"source":{"id":"https://openalex.org/S119727669","display_name":"Intelligent Decision Technologies","issn_l":"1872-4981","issn":["1872-4981","1875-8843"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Decision Technologies","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/A5103810313","display_name":"Nannan Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210151161","display_name":"Baoding University","ror":"https://ror.org/04asgtj30","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151161"]},{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Nannan Huang","raw_affiliation_strings":["Party Committee Teacher Work Department (Baoding) Human Resources Department (Baoding), North China Electric Power University, Baoding, China"],"affiliations":[{"raw_affiliation_string":"Party Committee Teacher Work Department (Baoding) Human Resources Department (Baoding), North China Electric Power University, Baoding, China","institution_ids":["https://openalex.org/I4210151161","https://openalex.org/I153473198"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100422603","display_name":"Xue Wang","orcid":"https://orcid.org/0000-0003-3943-6998"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]},{"id":"https://openalex.org/I4210151161","display_name":"Baoding University","ror":"https://ror.org/04asgtj30","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151161"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xue Wang","raw_affiliation_strings":["Party Committee Teacher Work Department (Baoding) Human Resources Department (Baoding), North China Electric Power University, Baoding, China"],"affiliations":[{"raw_affiliation_string":"Party Committee Teacher Work Department (Baoding) Human Resources Department (Baoding), North China Electric Power University, Baoding, China","institution_ids":["https://openalex.org/I4210151161","https://openalex.org/I153473198"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5103810313"],"corresponding_institution_ids":["https://openalex.org/I153473198","https://openalex.org/I4210151161"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20097382,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"3","first_page":"1841","last_page":"1853"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13812","display_name":"AI and HR Technologies","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1407","display_name":"Organizational Behavior and Human Resource Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13812","display_name":"AI and HR Technologies","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1407","display_name":"Organizational Behavior and Human Resource Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14413","display_name":"Advanced Technologies in Various Fields","score":0.9919000267982483,"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/T13345","display_name":"Advanced Technologies and Applied Computing","score":0.9836000204086304,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/pooling","display_name":"Pooling","score":0.6654383540153503},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6635409593582153},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6374886631965637},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.5974193215370178},{"id":"https://openalex.org/keywords/f1-score","display_name":"F1 score","score":0.5939674377441406},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5753223896026611},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5735459327697754},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5221210718154907},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.5193737149238586},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4199731647968292},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4108361601829529},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.1195543110370636}],"concepts":[{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6654383540153503},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6635409593582153},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6374886631965637},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.5974193215370178},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.5939674377441406},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5753223896026611},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5735459327697754},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5221210718154907},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.5193737149238586},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4199731647968292},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4108361601829529},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.1195543110370636},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/idt-240670","is_oa":false,"landing_page_url":"https://doi.org/10.3233/idt-240670","pdf_url":null,"source":{"id":"https://openalex.org/S119727669","display_name":"Intelligent Decision Technologies","issn_l":"1872-4981","issn":["1872-4981","1875-8843"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Decision Technologies","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.699999988079071,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2909518331","https://openalex.org/W2917965728","https://openalex.org/W2922150113","https://openalex.org/W2940702111","https://openalex.org/W2981825191","https://openalex.org/W2990456352","https://openalex.org/W3014267838","https://openalex.org/W3017037418","https://openalex.org/W3022550801","https://openalex.org/W3082287652","https://openalex.org/W3129743314","https://openalex.org/W3158279203","https://openalex.org/W3166459169","https://openalex.org/W3193781397","https://openalex.org/W3197617138","https://openalex.org/W4254436964","https://openalex.org/W4312759853","https://openalex.org/W6761627841","https://openalex.org/W6782247977","https://openalex.org/W6795503112","https://openalex.org/W6800046766"],"related_works":["https://openalex.org/W2967733078","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W2885778889","https://openalex.org/W4310224730","https://openalex.org/W2766514146","https://openalex.org/W4289703016","https://openalex.org/W2885516856","https://openalex.org/W3094138326"],"abstract_inverted_index":{"The":[0,38,69,92,104,139,189,230],"study":[1,112],"proposes":[2],"a":[3,7,13,22,199,220],"new":[4,140,178,196],"algorithm":[5,11,27,39,74,93,141,147,154,179,234],"combining":[6],"gradient":[8,47,144],"boosting":[9,48,145],"tree":[10,87,146],"with":[12,50,77,198,224],"hybrid":[14,56,106,150],"convolutional":[15,57,151],"neural":[16,58,152],"network":[17,153],"in":[18,110,155],"order":[19],"to":[20,28,82,90,219],"design":[21],"better":[23],"human":[24],"resource":[25],"recommendation":[26,201,228],"solve":[29],"the":[30,41,51,61,66,73,78,85,96,111,117,125,143,149,165,168,171,177,186,195,215,236],"problem":[31],"of":[32,46,55,63,65,131,157,164,167,176,185,194,203,214,222,240],"employment":[33],"difficulties":[34],"and":[35,84,100,122,128,136,148,159,162,173,191,207,238],"recruitment":[36],"difficulties.":[37],"combines":[40],"excellent":[42,52],"feature":[43],"transformation":[44],"ability":[45,54],"trees":[49],"classification":[53],"networks,":[59],"complementing":[60],"shortcomings":[62],"each":[64],"two":[67],"algorithms.":[68,229],"outcomes":[70],"showed":[71],"that":[72],"performed":[75],"best":[76],"learning":[79],"rate":[80],"set":[81,89],"0.3":[83],"maximum":[86],"depth":[88],"3.":[91],"now":[94],"has":[95],"lowest":[97],"loss":[98],"percentage":[99],"highest":[101],"F1-Score":[102,129,160,174,192],"value.":[103],"maximum-median":[105],"pooling":[107,119,133],"approach":[108],"used":[109],"had":[113,124],"considerable":[114],"improvements":[115],"over":[116],"algorithm\u2019s":[118],"strategy":[120],"(PS),":[121],"it":[123,223],"greatest":[126],"recall":[127,158,172,190],"values":[130,175,193],"all":[132],"strategies":[134],"(0.8108":[135],"0.7418,":[137],"respectively).":[138],"outperformed":[142],"terms":[156],"values,":[161],"regardless":[163],"length":[166,202],"job":[169,200],"recommendation,":[170],"were":[180,205],"consistently":[181],"higher":[182],"than":[183,212],"those":[184,213],"old":[187],"algorithm.":[188],"algorithm,":[197],"70,":[204],"0.8198":[206],"0.7432,":[208],"respectively,":[209],"both":[210],"greater":[211],"other":[216,225],"algorithms,":[217],"according":[218],"comparison":[221],"conventional":[226],"HR":[227,241],"study\u2019s":[231],"newly":[232],"created":[233],"increases":[235],"efficacy":[237],"precision":[239],"suggestions.":[242]},"counts_by_year":[],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}
