A hierarchical similarity based job recommendation service framework for university students

When people want to move to a new job, it is often difficult since there is too much job information available. To select an appropriate job and then submit a resume is tedious. It is particularly difficult for university students since they normally do not have any work experience and also are unfamiliar with the job market. To deal with the information overload for students during their transition into work, a job recommendation system can be very valuable. In this research, after fully investigating the pros and cons of current job recommendation systems for university students, we propose a student profiling based re-ranking framework. In this system, the students are recommended a list of potential jobs based on those who have graduated and obtained job offers over the past few years. Furthermore, recommended employers are also used as input for job recommendation result re-ranking. Our experimental study on real recruitment data over the past four years has shown this method’s potential.

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