An improvement of recommender system to find appropriate candidate for recruitment with colloborative filtering

Abstract

Recruitment is a significant process that affects to organizational performance. Recruiters expect to meet the most appropriate employee for the right job, but a large number of resumes make more difficult to their decision. For this reason, this paper proposed the recommender system to support recruiter in the decision and manage recruitments. The two techniques include matching and collaborative filtering. In the matching process, it compares the profile data and takes a score in order to rank the candidates. However, the scoring remains some problem that candidate scores are low dispersion. Therefore, the collaborative filtering technique was used to solve scoring problem. By applying this technique, the results shown that the scores were adjusted the distinction. Thus, the collaborative filtering could improve the score dispersion and easy to identify the most appropriate candidates, who had the best required qualification.