{"id":"https://openalex.org/W4206266858","doi":"https://doi.org/10.1109/bigdata52589.2021.9672057","title":"An Explainable Person-Job Fit Model Incorporating Structured Information","display_name":"An Explainable Person-Job Fit Model Incorporating Structured Information","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4206266858","doi":"https://doi.org/10.1109/bigdata52589.2021.9672057"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata52589.2021.9672057","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9672057","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-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/A5056547529","display_name":"Yunchong Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yunchong Zhang","raw_affiliation_strings":["Ningbo University, Ningbo, China"],"affiliations":[{"raw_affiliation_string":"Ningbo University, Ningbo, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030910124","display_name":"Baisong Liu","orcid":"https://orcid.org/0000-0001-5455-279X"},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baisong Liu","raw_affiliation_strings":["Ningbo University, Ningbo, China"],"affiliations":[{"raw_affiliation_string":"Ningbo University, Ningbo, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004828717","display_name":"Jiangbo Qian","orcid":"https://orcid.org/0000-0003-4245-3246"},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangbo Qian","raw_affiliation_strings":["Ningbo University, Ningbo, China"],"affiliations":[{"raw_affiliation_string":"Ningbo University, Ningbo, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021881680","display_name":"Jiangcheng Qin","orcid":"https://orcid.org/0000-0002-7705-6040"},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangcheng Qin","raw_affiliation_strings":["Ningbo University, Ningbo, China"],"affiliations":[{"raw_affiliation_string":"Ningbo University, Ningbo, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100639251","display_name":"Xueyuan Zhang","orcid":"https://orcid.org/0000-0001-5617-1640"},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueyuan Zhang","raw_affiliation_strings":["Ningbo University, Ningbo, China"],"affiliations":[{"raw_affiliation_string":"Ningbo University, Ningbo, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070143572","display_name":"Xueyong Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueyong Jiang","raw_affiliation_strings":["Ningbo University, Ningbo, China"],"affiliations":[{"raw_affiliation_string":"Ningbo University, Ningbo, China","institution_ids":["https://openalex.org/I109935558"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5056547529"],"corresponding_institution_ids":["https://openalex.org/I109935558"],"apc_list":null,"apc_paid":null,"fwci":0.5026,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.67330342,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3571","last_page":"3579"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9976000189781189,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9923999905586243,"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/computer-science","display_name":"Computer science","score":0.7871478796005249},{"id":"https://openalex.org/keywords/seekers","display_name":"Seekers","score":0.640200138092041},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6003180742263794},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.547124981880188},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.502723217010498},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.49265605211257935},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3778434991836548},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3398894667625427},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.333523154258728},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32024848461151123}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7871478796005249},{"id":"https://openalex.org/C2776493517","wikidata":"https://www.wikidata.org/wiki/Q1479542","display_name":"Seekers","level":2,"score":0.640200138092041},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6003180742263794},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.547124981880188},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.502723217010498},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.49265605211257935},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3778434991836548},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3398894667625427},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.333523154258728},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32024848461151123},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","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/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata52589.2021.9672057","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9672057","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.7200000286102295}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322605","display_name":"Ningbo University","ror":"https://ror.org/03et85d35"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W1966443646","https://openalex.org/W2250966211","https://openalex.org/W2774963710","https://openalex.org/W2798392716","https://openalex.org/W2798456655","https://openalex.org/W2798693700","https://openalex.org/W2799265169","https://openalex.org/W2806675864","https://openalex.org/W2810391274","https://openalex.org/W2890410227","https://openalex.org/W2893564970","https://openalex.org/W2901323180","https://openalex.org/W2920180483","https://openalex.org/W2949615363","https://openalex.org/W2952396276","https://openalex.org/W2963749936","https://openalex.org/W2971133212","https://openalex.org/W2989031759","https://openalex.org/W3034292689","https://openalex.org/W3093581739","https://openalex.org/W3094607200","https://openalex.org/W3099022409","https://openalex.org/W3100612294","https://openalex.org/W3101567279","https://openalex.org/W3138819813","https://openalex.org/W3140267674","https://openalex.org/W6632455782"],"related_works":["https://openalex.org/W2390017477","https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W3094895221","https://openalex.org/W2352448290","https://openalex.org/W4390273403","https://openalex.org/W2380820513","https://openalex.org/W4386781444","https://openalex.org/W2052925698","https://openalex.org/W2913146933"],"abstract_inverted_index":{"As":[0],"the":[1,11,54,80,83,87,113,118,128,132,149],"number":[2],"of":[3,15,20,82,89,99,159],"online":[4],"job":[5,135,139,150,178],"postings":[6],"and":[7,13,38,45,76,78,126,137,152,156,176],"users":[8],"grows":[9],"dramatically,":[10],"accuracy":[12],"explainability":[14],"personjob":[16,25],"fit":[17,26,60,109],"systems":[18],"are":[19],"increasing":[21],"concern.":[22],"An":[23],"explainable":[24,107],"system":[27,47],"can":[28],"show":[29,168],"reasons":[30,180],"when":[31],"making":[32],"recommendations":[33],"to":[34,96,146],"both":[35,154,182],"Human":[36],"Resources":[37],"Job":[39],"Seekers,":[40],"building":[41],"trust":[42],"between":[43,131],"uses":[44],"recommendation":[46,51,160,179],"while":[48],"providing":[49],"accurate":[50],"results.":[52],"However,":[53],"existing":[55,173],"research":[56],"on":[57,63,112,163],"content-based":[58],"person-job":[59,108],"mainly":[61],"focuses":[62],"1)":[64],"dealing":[65],"with":[66],"unstructured":[67,138,157],"statements":[68],"without":[69],"effectively":[70],"using":[71],"structured":[72,134,155],"information":[73],"in":[74],"resumes":[75],"jobs,":[77],"2)":[79],"explanations":[81],"model":[84,110,117,148,171],"stay":[85],"at":[86,181],"level":[88],"giving":[90],"a":[91,97,122,142,164],"few":[92],"sentences,":[93],"which":[94],"leads":[95],"lack":[98],"explanations.":[100],"In":[101],"this":[102],"paper,":[103],"we":[104],"propose":[105],"an":[106],"based":[111],"attention":[114,124,144],"mechanism.":[115],"We":[116],"resume":[119],"text":[120,140],"through":[121,141],"hierarchical":[123],"mechanism":[125,145],"capture":[127],"semantic":[129],"connections":[130],"resume,":[133],"text,":[136],"collaborative":[143],"better":[147],"content":[151],"provide":[153],"levels":[158],"explanation.":[161],"Experiments":[162],"large":[165],"real":[166],"dataset":[167],"that":[169],"our":[170],"outperforms":[172],"baseline":[174],"models":[175],"provides":[177],"levels.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-02-27T16:54:17.756197","created_date":"2025-10-10T00:00:00"}