Vers un cadre ontologique pour la gestion des comp'etences : `a des fins de formation, de recrutement, de m'etier, ou de recherches associ'ees
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Abstract (arXiv)
The rapid transformation of the labor market, driven by technological advancements and the digital economy, requires continuous competence development and constant adaptation. In this context, traditional competence management systems lack interoperability, adaptability, and semantic understanding, making it difficult to align individual competencies with labor market needs and training programs. This paper proposes an ontology-based framework for competence management, enabling a structured representation of competencies, occupations, and training programs. By leveraging ontological models and semantic reasoning, this framework aims to enhance the automation of competence-to-job matching, the personalization of learning recommendations, and career planning. This study discusses the design, implementation, and potential applications of the framework, focusing on competence training programs, job searching, and finding competent individuals.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 8 Jul 2025.
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Citing papers per year: 2025: 1; 2026: 2.
3 papers.
- 2025Automated Skill Decomposition Meets Expert Ontologies: Bridging the Granularity Gap with LLMscited by 4
- 2026KG-First, LLM-Fallback: A Hybrid Microservice for Grounded Skill Search and Explanationcited by 0
- 2026From Student Risk Prediction to SC2R: Semantics-Constrained Counterfactual Recourse for Educational Decision Supportcited by 0
- 2026From Student Risk Prediction to SC2R: Semantics-Constrained Counterfactual Recourse for Educational Decision Support18 Aug 2026
- 2026KG-First, LLM-Fallback: A Hybrid Microservice for Grounded Skill Search and Explanation2 May 2026
- 2025Automated Skill Decomposition Meets Expert Ontologies: Bridging the Granularity Gap with LLMs13 Oct 2025