{"id":"https://openalex.org/W7204109752","doi":"https://doi.org/10.1038/s41598-026-54959-2","title":"Automated resume screening using machine learning: an ensemble-based approach for efficient candidate selection","display_name":"Automated resume screening using machine learning: an ensemble-based approach for efficient candidate selection","publication_year":2026,"publication_date":"2026-08-24","ids":{"openalex":"https://openalex.org/W7204109752","doi":"https://doi.org/10.1038/s41598-026-54959-2"},"language":"en","primary_location":{"id":"doi:10.1038/s41598-026-54959-2","doi":"https://doi.org/10.1038/s41598-026-54959-2","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41598-026-54959-2","pdf_url":"https://www.nature.com/articles/s41598-026-54959-2_reference.pdf","source":{"id":"https://openalex.org/S196734849","display_name":"Scientific Reports","issn_l":"2045-2322","issn":["2045-2322"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Reports","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.nature.com/articles/s41598-026-54959-2_reference.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134917503","display_name":"Muhammad Hamid","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4387153245","display_name":"Government College Women University Sialkot","ror":"https://ror.org/00bqnfa53","country_code":null,"type":"government","lineage":["https://openalex.org/I4387153245"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Muhammad Hamid","raw_affiliation_strings":["Department of Computer Science, Government College Women University Sialkot, Sialkot, 51310, Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Government College Women University Sialkot, Sialkot, 51310, Pakistan","institution_ids":["https://openalex.org/I4387153245"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078943371","display_name":"Fahima Hajjej","orcid":"https://orcid.org/0000-0003-1709-5790","observed_orcids":["https://orcid.org/0000-0003-1709-5790"]},"institutions":[{"id":"https://openalex.org/I106778892","display_name":"Princess Nourah bint Abdulrahman University","ror":"https://ror.org/05b0cyh02","country_code":"SA","type":"education","lineage":["https://openalex.org/I106778892"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Fahima Hajjej","raw_affiliation_strings":["Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia","institution_ids":["https://openalex.org/I106778892"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063580605","display_name":"Ala Saleh Alluhaidan","orcid":"https://orcid.org/0000-0001-6829-9705","observed_orcids":["https://orcid.org/0000-0001-6829-9705","https://orcid.org/0009-0002-5877-5119","https://orcid.org/0009-0008-6177-6722"]},"institutions":[{"id":"https://openalex.org/I106778892","display_name":"Princess Nourah bint Abdulrahman University","ror":"https://ror.org/05b0cyh02","country_code":"SA","type":"education","lineage":["https://openalex.org/I106778892"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Ala Saleh Alluhaidan","raw_affiliation_strings":["Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia","institution_ids":["https://openalex.org/I106778892"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5147967861","display_name":"Reem Gharwi","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I106778892","display_name":"Princess Nourah bint Abdulrahman University","ror":"https://ror.org/05b0cyh02","country_code":"SA","type":"education","lineage":["https://openalex.org/I106778892"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Reem Gharwi","raw_affiliation_strings":["Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia","institution_ids":["https://openalex.org/I106778892"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5078943371"],"corresponding_institution_ids":["https://openalex.org/I106778892"],"apc_list":{"value":2690,"currency":"USD","value_usd":2690},"apc_paid":{"value":2690,"currency":"USD","value_usd":2690},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.65700943,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13812","display_name":"AI and HR Technologies","score":0.9994999766349792,"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":0.9994999766349792,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12415","display_name":"Employer Branding and e-HRM","score":9.999999747378752e-05,"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/automated-resume-screening","display_name":"automated resume screening","score":0.8510000109672546},{"id":"https://openalex.org/keywords/resume-classification","display_name":"resume classification","score":0.953000009059906},{"id":"https://openalex.org/keywords/recruitment","display_name":"recruitment","score":0.42500001192092896},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"ensemble learning","score":0.9190000295639038},{"id":"https://openalex.org/keywords/soft-voting","display_name":"soft voting","score":0.9110000133514404},{"id":"https://openalex.org/keywords/talent-acquisition","display_name":"talent acquisition","score":0.6499999761581421},{"id":"https://openalex.org/keywords/algorithmic-fairness","display_name":"algorithmic fairness","score":0.9079999923706055},{"id":"https://openalex.org/keywords/interpretability","display_name":"interpretability","score":0.7670000195503235},{"id":"https://openalex.org/keywords/web-based-prototype","display_name":"web-based prototype","score":0.6800000071525574}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8269000053405762},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7876999974250793},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.65420001745224},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.6326000094413757},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5860000252723694},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5788999795913696},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5633999705314636},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.527899980545044},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5148000121116638},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4846000075340271},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4034000039100647},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.40310001373291016},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.39079999923706055},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.3578000068664551},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.35440000891685486},{"id":"https://openalex.org/C162040801","wikidata":"https://www.wikidata.org/wiki/Q799897","display_name":"Bootstrap aggregating","level":2,"score":0.34439998865127563},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.34369999170303345},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.3246999979019165},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3070000112056732},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.2980000078678131},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.29260000586509705},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.2808000147342682},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.2786000072956085},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.25519999861717224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1038/s41598-026-54959-2","doi":"https://doi.org/10.1038/s41598-026-54959-2","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41598-026-54959-2","pdf_url":"https://www.nature.com/articles/s41598-026-54959-2_reference.pdf","source":{"id":"https://openalex.org/S196734849","display_name":"Scientific Reports","issn_l":"2045-2322","issn":["2045-2322"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Reports","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1038/s41598-026-54959-2","doi":"https://doi.org/10.1038/s41598-026-54959-2","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41598-026-54959-2","pdf_url":"https://www.nature.com/articles/s41598-026-54959-2_reference.pdf","source":{"id":"https://openalex.org/S196734849","display_name":"Scientific Reports","issn_l":"2045-2322","issn":["2045-2322"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Reports","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.4074000120162964}],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320337220","display_name":"Deanship of Scientific Research, Princess Nourah Bint Abdulrahman University","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204109752.pdf","grobid_xml":"https://content.openalex.org/works/W7204109752.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"scale":[1],"recruitment":[2],"is":[3,14,223],"time-consuming":[4],"and":[5,55,177,215,228],"results":[6,218],"in":[7,78,143,211],"inefficiencies":[8],"where":[9],"manual":[10],"screening":[11],"of":[12,34,69,108,132,174,180],"resumes":[13],"used.":[15],"This":[16],"study":[17],"proposed":[18,90],"a":[19,39,79,100,150,161,171,200],"novel":[20],"Machine":[21],"Learning":[22],"(ML)":[23],"based":[24,196],"ensemble":[25,84,91,166],"framework":[26,85,92,146,222],"for":[27,235],"resume":[28,213],"classification":[29,214],"to":[30,61,82,123,138,188,207],"improve":[31],"the":[32,67,72,125,130,133,140,145,194,221],"process":[33],"recruitment.":[35],"The":[36,89,165,217],"research":[37],"has":[38],"two-phase":[40],"experimental":[41],"design.":[42],"First,":[43],"several":[44],"ML":[45],"classifiers":[46,98],"such":[47],"as":[48],"Logistic":[49],"Regression,":[50],"Decision":[51],"Trees,":[52],"Naive":[53],"Bayes":[54],"Random":[56],"Forest":[57],"have":[58],"been":[59],"benchmarked":[60],"determine":[62],"baseline":[63],"performance.":[64],"Secondly":[65],"on":[66,99,149,197],"basis":[68],"these":[70],"results,":[71],"best":[73],"performing":[74],"models":[75],"were":[76,121],"merged":[77],"strategic":[80],"manner":[81],"form":[83],"using":[86],"soft-voting":[87],"mechanism.":[88],"performed":[93],"significantly":[94],"better":[95],"than":[96],"standalone":[97],"standard":[101],"benchmark":[102],"data":[103],"set":[104],"with":[105,160,170],"an":[106,178,183],"accuracy":[107],"98.44%":[109],"(5-fold":[110],"CV":[111],"mean:":[112],"97.47%":[113],"\u00b11.00%).":[114],"Paired":[115],"T-tests":[116],"(":[117,156],"p":[118],"<":[119],"0.05)":[120],"used":[122,187],"ensure":[124],"statistical":[126],"significance,":[127],"which":[128,192],"confirmed":[129],"reliability":[131],"performance":[134,172],"gains.":[135],"In":[136],"order":[137],"resolve":[139],"robustness":[141],"gap":[142],"literature,":[144],"was":[147,186,205],"tested":[148],"new":[151],"curated":[152],"expert-labeled":[153],"heterogeneous":[154],"dataset":[155],"N":[157],"=":[158],"598)":[159],"Zero-Shot":[162],"testing":[163],"protocol.":[164],"showed":[167],"outstanding":[168],"stability":[169],"decrease":[173],"just":[175],"1.10%,":[176],"F1-score":[179],"0.99.":[181],"Additionally,":[182],"interpretability":[184],"audit":[185],"confirm":[189],"algorithmic":[190],"fairness,":[191],"guarantees":[193],"selection":[195],"merit.":[198],"Finally,":[199],"full":[201],"functional":[202],"web-based":[203],"prototype":[204],"created":[206],"illustrate":[208],"practical":[209],"viability":[210],"real-time":[212],"recommendation.":[216],"prove":[219],"that":[220],"not":[224],"only":[225],"highly":[226],"accurate":[227],"statistically":[229],"reliable,":[230],"but":[231],"also":[232],"practically":[233],"implementable":[234],"real-world":[236],"talent":[237],"acquisition.":[238]},"counts_by_year":[],"updated_date":"2026-10-08T09:06:37.294493","created_date":"2026-08-25T00:00:00"}
