{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T23:54:57Z","timestamp":1773273297964,"version":"3.50.1"},"reference-count":33,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T00:00:00Z","timestamp":1773187200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Human resource management is a strategic axis for organizations, especially in contexts where artificial intelligence (AI) tools, such as natural language processing (NLP), play a fundamental role. Recruiting external applicants from large CV repositories requires consistent screening. The proposed methodology involves leveraging an existing curriculum vitae (CV) repository, structuring and indexing the data within a vector-based knowledge base, and applying retrieval techniques to identify candidates that satisfy role-specific criteria. Using 5029 CVs as benchmarks, we evaluate 3 queries, 3 variables (Degree, Skills, Experience), and 7 scenarios. Sampling n = 76 CVs for Queries 1\u20132 and n = 350 CVs for Query 3. The proposed approach achieved consistently high specificity across scenarios and query profiles, while sensitivity showed the largest fluctuations, particularly under single-requirement configurations. Across all queries and scenarios, accuracy ranged 65.79\u201398.00%, specificity 86.67\u2013100.00%, and sensitivity 0.00\u201394.92%, while error rates decreased from 34.21% to 2.00% as constraint strictness increased. Sensitivity fluctuated most under single-requirement settings, and Experience-only screening showed the weakest selection behavior. Moreover, the results indicate that the ability to confirm suitable candidates is sensitive to query formulation, since non-standard role naming, experience phrasing, and other lexical variations can reduce the system\u2019s capacity to detect positive evidence. Overall, these findings indicate that a knowledge-base-centered design enables consistent and interpretable requirement-driven candidate screening and provides a quantitative baseline for future improvements in recruitment-oriented retrieval systems.<\/jats:p>","DOI":"10.3390\/info17030279","type":"journal-article","created":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T09:00:37Z","timestamp":1773219637000},"page":"279","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Knowledge-Based Design Methodology for Human Resources Information Management"],"prefix":"10.3390","volume":"17","author":[{"given":"Sof\u00eda","family":"Morales-Zaleta","sequence":"first","affiliation":[{"name":"Divisi\u00f3n de Estudios de Posgrado e Investigaci\u00f3n, Tecnol\u00f3gico Nacional de M\u00e9xico\/Instituto Tecnol\u00f3gico de Ciudad Madero, Ciudad Madero 89440, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2496-0009","authenticated-orcid":false,"given":"Mirna Patricia","family":"Ponce-Flores","sequence":"additional","affiliation":[{"name":"Divisi\u00f3n de Estudios de Posgrado e Investigaci\u00f3n, Tecnol\u00f3gico Nacional de M\u00e9xico\/Instituto Tecnol\u00f3gico de Ciudad Madero, Ciudad Madero 89440, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guadalupe","family":"Castilla-Valdez","sequence":"additional","affiliation":[{"name":"Divisi\u00f3n de Estudios de Posgrado e Investigaci\u00f3n, Tecnol\u00f3gico Nacional de M\u00e9xico\/Instituto Tecnol\u00f3gico de Ciudad Madero, Ciudad Madero 89440, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan","family":"Frausto-Sol\u00eds","sequence":"additional","affiliation":[{"name":"Divisi\u00f3n de Estudios de Posgrado e Investigaci\u00f3n, Tecnol\u00f3gico Nacional de M\u00e9xico\/Instituto Tecnol\u00f3gico de Ciudad Madero, Ciudad Madero 89440, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3699-4436","authenticated-orcid":false,"given":"Juan Javier Gonz\u00e1lez-","family":"Barbosa","sequence":"additional","affiliation":[{"name":"Divisi\u00f3n de Estudios de Posgrado e Investigaci\u00f3n, Tecnol\u00f3gico Nacional de M\u00e9xico\/Instituto Tecnol\u00f3gico de Ciudad Madero, Ciudad Madero 89440, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erika","family":"Alarc\u00f3n-Ruiz","sequence":"additional","affiliation":[{"name":"Divisi\u00f3n de Estudios de Posgrado e Investigaci\u00f3n, Tecnol\u00f3gico Nacional de M\u00e9xico\/Instituto Tecnol\u00f3gico de Ciudad Madero, Ciudad Madero 89440, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/j.aej.2025.02.043","article-title":"Knowledge graph construction and talent competency prediction for human resource management","volume":"121","author":"Yang","year":"2025","journal-title":"Alex. 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