{"id":"https://openalex.org/W4411688095","doi":"https://doi.org/10.1109/access.2025.3583324","title":"Deep Learning-Driven Labor Education and Skill Assessment: A Big Data Approach for Optimizing Workforce Development and Industrial Relations","display_name":"Deep Learning-Driven Labor Education and Skill Assessment: A Big Data Approach for Optimizing Workforce Development and Industrial Relations","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4411688095","doi":"https://doi.org/10.1109/access.2025.3583324"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3583324","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3583324","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3583324","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101306736","display_name":"Dan Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dan Peng","raw_affiliation_strings":["School of Marxism, China University of Mining and Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0006-7678-8238","affiliations":[{"raw_affiliation_string":"School of Marxism, China University of Mining and Technology, Beijing, China","institution_ids":["https://openalex.org/I25757504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101306736"],"corresponding_institution_ids":["https://openalex.org/I25757504"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":6.8816,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.96388334,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"13","issue":null,"first_page":"111064","last_page":"111086"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13812","display_name":"AI and HR Technologies","score":0.7635999917984009,"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":0.7635999917984009,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/workforce","display_name":"Workforce","score":0.748045802116394},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6535079479217529},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6524862051010132},{"id":"https://openalex.org/keywords/workforce-development","display_name":"Workforce development","score":0.5613124966621399},{"id":"https://openalex.org/keywords/industrial-relations","display_name":"Industrial relations","score":0.4779134690761566},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.4439052641391754},{"id":"https://openalex.org/keywords/workforce-planning","display_name":"Workforce planning","score":0.42081156373023987},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41125795245170593},{"id":"https://openalex.org/keywords/engineering-management","display_name":"Engineering management","score":0.3267422318458557},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.323090136051178},{"id":"https://openalex.org/keywords/management","display_name":"Management","score":0.15696540474891663},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13916721940040588},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.1119500994682312},{"id":"https://openalex.org/keywords/economic-growth","display_name":"Economic growth","score":0.1081150472164154},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.09190371632575989}],"concepts":[{"id":"https://openalex.org/C2778139618","wikidata":"https://www.wikidata.org/wiki/Q13440398","display_name":"Workforce","level":2,"score":0.748045802116394},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6535079479217529},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6524862051010132},{"id":"https://openalex.org/C2779968149","wikidata":"https://www.wikidata.org/wiki/Q8034851","display_name":"Workforce development","level":3,"score":0.5613124966621399},{"id":"https://openalex.org/C38104776","wikidata":"https://www.wikidata.org/wiki/Q932071","display_name":"Industrial relations","level":2,"score":0.4779134690761566},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.4439052641391754},{"id":"https://openalex.org/C155663085","wikidata":"https://www.wikidata.org/wiki/Q1056396","display_name":"Workforce planning","level":3,"score":0.42081156373023987},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41125795245170593},{"id":"https://openalex.org/C110354214","wikidata":"https://www.wikidata.org/wiki/Q6314146","display_name":"Engineering management","level":1,"score":0.3267422318458557},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.323090136051178},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.15696540474891663},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13916721940040588},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.1119500994682312},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.1081150472164154},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.09190371632575989}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3583324","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3583324","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:20ad915ffc1d4c3e8f0df56509fb8dff","is_oa":true,"landing_page_url":"https://doaj.org/article/20ad915ffc1d4c3e8f0df56509fb8dff","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 111064-111086 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3583324","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3583324","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7200000286102295,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W2147618390","https://openalex.org/W2965373594","https://openalex.org/W3091746701","https://openalex.org/W3163650427","https://openalex.org/W3168997536","https://openalex.org/W3175855397","https://openalex.org/W3180181113","https://openalex.org/W3190268244","https://openalex.org/W3202948811","https://openalex.org/W4205158424","https://openalex.org/W4206250065","https://openalex.org/W4210819220","https://openalex.org/W4211234505","https://openalex.org/W4280636306","https://openalex.org/W4281491026","https://openalex.org/W4285225959","https://openalex.org/W4292055113","https://openalex.org/W4293728430","https://openalex.org/W4297498781","https://openalex.org/W4309563570","https://openalex.org/W4322766882","https://openalex.org/W4379781056","https://openalex.org/W4382246105","https://openalex.org/W4384156831","https://openalex.org/W4385245566","https://openalex.org/W4387912962","https://openalex.org/W4387974537","https://openalex.org/W4393153538","https://openalex.org/W4409363027","https://openalex.org/W4409736269","https://openalex.org/W4410049680","https://openalex.org/W6755207826","https://openalex.org/W6768021236","https://openalex.org/W6769627184","https://openalex.org/W6778883912","https://openalex.org/W6797160615","https://openalex.org/W6809646742","https://openalex.org/W6810738896","https://openalex.org/W6842011266","https://openalex.org/W6846254642","https://openalex.org/W6847076894","https://openalex.org/W6850625674","https://openalex.org/W6853172137","https://openalex.org/W6856289622","https://openalex.org/W6856755253","https://openalex.org/W6858453470","https://openalex.org/W6860637852","https://openalex.org/W6862184107","https://openalex.org/W6891937734","https://openalex.org/W6947906995"],"related_works":["https://openalex.org/W1979606825","https://openalex.org/W2094416892","https://openalex.org/W2315207623","https://openalex.org/W1961830499","https://openalex.org/W3000739386","https://openalex.org/W2563616480","https://openalex.org/W2535586030","https://openalex.org/W2199622948","https://openalex.org/W3135476795","https://openalex.org/W93508136"],"abstract_inverted_index":{"The":[0,74,107],"automation":[1],"of":[2,9,36,114,117,120,125,142],"resume":[3,20,62,98],"screening":[4,21,63],"is":[5],"a":[6,57,95,111],"critical":[7],"component":[8],"modern":[10],"recruitment":[11,72],"processes,":[12],"particularly":[13],"in":[14,39,103,145],"large":[15],"organizations.":[16],"Automated":[17],"systems":[18,144],"for":[19,60,85],"typically":[22],"involve":[23],"various":[24],"NLP":[25],"tasks":[26],"to":[27,70,156],"streamline":[28],"candidate":[29],"evaluation.":[30],"This":[31],"paper":[32],"investigates":[33],"the":[34,88,129,140,150],"application":[35],"LLM":[37,68],"models":[38,69,131],"automating":[40,61,146],"labor":[41],"education":[42],"and":[43,64,80,105,122,135],"skill":[44],"assessment,":[45],"focusing":[46],"on":[47,94],"optimizing":[48],"workforce":[49],"development":[50],"through":[51],"advanced":[52],"language":[53],"models.":[54,162],"We":[55],"propose":[56],"comprehensive":[58],"framework":[59],"grading,":[65],"utilizing":[66],"SOTA":[67],"enhance":[71],"processes.":[73],"proposed":[75],"system":[76],"integrates":[77],"information":[78],"extraction":[79],"summarization":[81],"tasks,":[82],"leveraging":[83],"LLMs":[84],"decision-making":[86],"throughout":[87],"hiring":[89],"process.":[90],"Our":[91],"experiments,":[92],"conducted":[93],"publicly":[96],"available":[97],"dataset,":[99],"demonstrate":[100],"significant":[101],"improvements":[102],"efficiency":[104],"accuracy.":[106],"LLaMA2-13B":[108,152],"model,":[109],"achieves":[110],"ROUGE-1":[112],"score":[113,124],"37.31,":[115],"ROUGE-2":[116],"15.04,":[118],"ROUGE-L":[119],"36.99,":[121],"BLEU":[123],"13.82,":[126],"significantly":[127],"outperforming":[128],"baseline":[130],"such":[132],"as":[133],"FLAN-T5":[134],"GPT-NeoX.":[136],"These":[137],"results":[138],"highlight":[139],"potential":[141],"LLM-based":[143],"labor-related":[147],"assessments,":[148],"with":[149],"fine-tuned":[151],"model":[153],"delivering":[154],"up":[155],"27%":[157],"better":[158],"performance":[159],"than":[160],"zero-shot":[161]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
