A comparison study for job recommendation

Abstract

Job recommender is a system that automatically returns a ranked list of suitable, prospective jobs for employees. It plays a significant role in connecting employees and employers. In order to choose a suitable algorithm to build the system, a comparison study of popular recommendation methods is conducted and reported in this paper. The experimental data crawled from vietnamworks.com, itviec.com and careerlink.vn. A subset includes 7623 jobs extracted for running experiment. There are totally 59 users who have joint in rating jobs as well as giving feedback to measure performance of different methods. The experimental results demonstrated that content based approach is outperform than other tradictional ones.