Authors : Sihem Bouhenniche, Sabrina Boudjedar, Hakim Mokeddem, Hamid Benachour

Over the last decade, several e-recruitment platforms have been developed, allowing users to publish their professional information (training, work history, career summary, etc.). However, representing this huge quantity of knowledge still limited. In this work, we present a method based on community detection and natural language processing techniques in order to generate a human resources “HR” ontology. The data used in the generation process is user’s profiles retrieved from the Algerian e-recruitment platform Emploitic.com(www.emploitic.com). Data includes occupations, skills and professional domains. Our main contribution appears in the identification of new relationships between these concepts using community detection in each area of work. The generated ontology has hierarchical relationships between skills, professions and professional domains. In order to evaluate the relevance of this ontology, we used both the manual method with experts in human resources domain and the automatic method through comparisons with existing HR-ontologies. The evaluation has shown promising results.