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Internet has become the primary medium for Human Resource Management, specifically job recruitment and employment process. Classical job recruitment portals on the Internet rely on the keyword based search technique in plain text to locate jobs. However, this technique results in high recall, low precision and without considering the semantic similarity between these keywords. Many researchers have proposed semantic matching approaches by developing ontologies as a reference to determine matching accuracy qualitatively, however these approaches do not quantify how closely matched applicants and employers are, based on core skills. This paper proposes a technique that uses an ontology based approach to enhance keyword searching by leveraging on the similarity between concepts in the ontology, which represent core skills needed and required for a job in order to determine how closely matched an applicant is to a job advertisement and vice-versa. This was achieved by developing a CV Ontology based on core skills, annotating applicant profiles and job profiles using a common vocabulary and modifying the semantic concept similarity algorithm to accurately compute and rank matching score between profiles when a query is performed. The results showed improvements of 54% and 36% for Recall and F-measure respectively, over .
Keywords: Ontology, Semantic, Algorithm, Core Skills, OWL