Leveraging Ontologies and Process Mining in Personalized Recruitment Recommendations

Authors

  • Naoual Smaili SI2M Laboratory, National Institute of Statistics and Applied Economics (INSEA), B.P. 6217, Rabat, 10112, Morocco
  • Zineb Lamghari Department of Computer Science, Faculty of Sciences, Mohammed V University in Rabat, Rabat 10000, Morocco

DOI:

https://doi.org/10.19139/soic-2310-5070-2536

Keywords:

Semantic process mining, Ontologies, Event-logs, Recruitment optimization

Abstract

This paper presents a novel approach to improve recruitment methods through a comprehensive examination of contextual data and process models. The primary focus is on refining the process by aligning it with candidate preferences. The method incorporates ontology and process mining to provide contextual and sequential recommendations, adapting hunting methods according to candidate requests. Using a recruitment ontology and connecting it with candidate assessments, the approach refines strategies using successful recruitment historical data. Conformance checking identifies similar process models, connecting the ontology of each activity for a detailed analysis. The results highlight the effectiveness of the method in adjusting recruitment strategies based on historical and contextual data, offering a comprehensive and flexible solution for efficient recruitment.

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Published

2025-05-28

How to Cite

Smaili, N., & Lamghari, Z. (2025). Leveraging Ontologies and Process Mining in Personalized Recruitment Recommendations. Statistics, Optimization & Information Computing, 15(2), 1068–1086. https://doi.org/10.19139/soic-2310-5070-2536

Issue

Vol. 15 No. 2 (2026): I2CEAI24

Section

Research Articles

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