A Personality Matching-aided Approach for Supervisor Recommendation (research-in-progress)

In educational field, finding a suitable supervisor is vitally important for a student’s research career. Students can acquire dynamic and continuous knowledge from supervisors. With the rapid proliferation of information technologies, there is amount of online information available for students. It poses challenges for them to quickly find relevant and useful information. Supervisor recommendation is a novel way to provide support for students to select appropriate dynamic knowledge resources. Current methods mainly mine the matching of objective information but pay scant attention on subjective personality matching which is crucial for effective communications among individuals. In this study, we propose a personality matching-aided recommendation approach to facilitate supervisor selections. Furthermore, the student-supervisor recommendation service has been implemented on ScholarMate 1 which is a research social network platform. A preliminary user study is designed to evaluate the proposed method. The results show that our approach outperforms three baseline methods.