A curriculum vitae or a résumé, in general, consists of personal details, education, work experience, qualifications, and references. The overall objective of this study was to extract such data as experience, features, and business and education information from résumés stored in human resources repositories. In this article, we propose an ontology-driven information extraction system that is planned to operate on several million free-format textual résumés to convert them to a structured and semantically enriched version for use in semantic data mining of data essential in human resources processes. The architecture and working mechanism of the system, similarity of the concept and matching techniques, and an inference mechanism are introduced, and a case study is presented.