{"id":15320,"date":"2026-06-03T19:28:00","date_gmt":"2026-06-03T19:28:00","guid":{"rendered":"https:\/\/new.exprivia.it\/sin-categoria\/system-for-matching-and-ranking-talents\/"},"modified":"2026-06-04T16:19:13","modified_gmt":"2026-06-04T16:19:13","slug":"system-for-matching-and-ranking-talents","status":"publish","type":"post","link":"https:\/\/www.exprivia.it\/es\/proyectos-de-investigacion\/system-for-matching-and-ranking-talents\/","title":{"rendered":"System for Matching And Ranking Talents"},"content":{"rendered":"<h2 style=\"margin-bottom: 5px; line-height: 1.3; font-size: 1.5em;\">Requisito<\/h2>\n<p>Optimiza el proceso de selecci\u00f3n mediante una soluci\u00f3n de Inteligencia de RRHH que integre motores de flujo de trabajo BPM sin c\u00f3digo y agentes de IA para identificar el mejor talento en un entorno laboral cada vez m\u00e1s competitivo.<\/p>\n<h2 style=\"margin-bottom: 5px; line-height: 1.3; font-size: 1.5em;\">Abstract progetto<\/h2>\n<p>El proyecto SMART naci\u00f3 de la necesidad de optimizar el proceso de selecci\u00f3n de personal, donde el tiempo y la calidad del reclutamiento son factores clave para identificar y contratar a los mejores talentos en el mercado laboral.<\/p>\n<p>Actualmente, la evaluaci\u00f3n de los candidatos se realiza manualmente, bas\u00e1ndose en la experiencia del reclutador y en cada puesto de trabajo individual. El enfoque actual es lento, desafiante y puede conducir a sesgos e inexactitudes en las evaluaciones finales. Adem\u00e1s, no permite evaluar la idoneidad del candidato en m\u00faltiples puestos. Como resultado, conlleva un alto riesgo de evaluaciones incorrectas, as\u00ed como la posibilidad de incurrir en falsos positivos y falsos negativos.<br \/>\nA esto se suma el uso de m\u00faltiples herramientas de software, que dificultan el intercambio y seguimiento de informaci\u00f3n entre reclutadores, responsables de contrataci\u00f3n y candidatos.   <\/p>\n<p>La plataforma SMART integra una soluci\u00f3n BPM (Business Process Management) sin c\u00f3digo para el modelado digital y la ejecuci\u00f3n de todo el proceso de reclutamiento, orquestando las actividades e interacciones de los actores de RRHH. A diferencia de las soluciones verticales, SMART garantiza flexibilidad e integraci\u00f3n total con el contexto organizativo existente.<\/p>\n<p>Un sistema multiagente basado en los recursos humanos de agentes de IA permite la evaluaci\u00f3n r\u00e1pida y simult\u00e1nea de los candidatos en las fases de Selecci\u00f3n, Emparejamiento de Puestos y Clasificaci\u00f3n.<br \/>\nEl an\u00e1lisis de un candidato considera no solo el contenido expresado en el CV, como habilidades, experiencia laboral y acad\u00e9mica, sino tambi\u00e9n informaci\u00f3n adicional como el perfil profesional de LinkedIn, informaci\u00f3n p\u00fablica disponible en l\u00ednea, certificaciones y certificados, habilidades t\u00e9cnicas y blandas validadas mediante cuestionarios previos y entrevistas. Todo esto, en comparaci\u00f3n con el perfil ideal expresado en el puesto de trabajo de manera justa e imparcial. <\/p>\n<p>Los agentes de RRHH operan seg\u00fan un enfoque simbi\u00f3tico humano-IA, proporcionando sugerencias, retroalimentaci\u00f3n y explicabilidad de los resultados para apoyar las decisiones de los reclutadores. De este modo, humanos e IA trabajan codo con codo y ambas partes aprenden y se adaptan mutuamente. <\/p>\n<h2 style=\"margin-bottom: 5px; line-height: 1.3; font-size: 1.5em;\">Beneficios esperados<\/h2>\n<ol>\n<li>Recogida automatizada de CVs de m\u00faltiples fuentes de datos<\/li>\n<li>Reducci\u00f3n del tiempo de an\u00e1lisis curricular<\/li>\n<li>Reducir la p\u00e9rdida de aplicaciones \u00fatiles<\/li>\n<li>Reducci\u00f3n general del tiempo de contrataci\u00f3n<\/li>\n<li>Mayor precisi\u00f3n en la correspondencia de trabajos<\/li>\n<li>Optimizaci\u00f3n de los costes de reclutamiento<\/li>\n<li>Mejorando la experiencia del candidato<\/li>\n<\/ol>\n<p><strong>Resultados esperados<\/strong><\/p>\n<ul>\n<li>Prototipo de software de inteligencia de RRHH compuesto por los m\u00f3dulos: (i) Interfaz de usuario; (ii) Recogida y gesti\u00f3n de datos; (iii) Procesamiento y An\u00e1lisis de Datos; (iv) Agentes de Motores de IA y RRHH; (v) Flujo de trabajo BPM No-Code     <\/li>\n<li>Informe t\u00e9cnico a trav\u00e9s de entregables del proyecto<\/li>\n<li>Difusi\u00f3n y difusi\u00f3n de resultados a trav\u00e9s de eventos, conferencias y art\u00edculos cient\u00edficos<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Requisito Optimiza el proceso de selecci\u00f3n mediante una soluci\u00f3n de  [&#8230;]<\/p>\n","protected":false},"author":2,"featured_media":15319,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"categories":[189],"tags":[151,137],"class_list":["post-15320","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-proyectos-de-investigacion","tag-administracion-publica","tag-inteligencia-artificial"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.7 (Yoast SEO v27.7) - 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