In the recruitment process, manually selecting suitable candidates from curriculum vitae (CVs) for a job description (JD) is both time-consuming and expensive. Traditional keyword-based methods struggle to capture skill semantics, prompting the development of more advanced JD-CV matching systems. This paper aims to investigate and construct an ontology-based skills recommendation system, with objectives including creating a skills ontology and developing skills matching methods for JD-CV pairs. …
Read moreIn the recruitment process, manually selecting suitable candidates from curriculum vitae (CVs) for a job description (JD) is both time-consuming and expensive. Traditional keyword-based methods struggle to capture skill semantics, prompting the development of more advanced JD-CV matching systems. This paper aims to investigate and construct an ontology-based skills recommendation system, with objectives including creating a skills ontology and developing skills matching methods for JD-CV pairs. The objective of our approach is to enhance the accuracy and contextual relevance of recommendations by utilizing the proposed score. The proposed skills ontology and skills matching strategies are applied to a real dataset in Vietnam. The results of our study can automatically recommend a list of CVs for a given JD. Furthermore, the findings indicate that our proposed model surpasses comparative approaches by a margin of at least 1% to 5%. Overall, the study demonstrates the potential of utilizing ontology-based approaches to offer a practical solution for enhancing hiring practices.
