A Novel Approach to Rank Jobs for a Jobseeker

Abstract

Recruitment is one of the major tasks for the HR industry. As it offers numerous job opportunities at various locations, it is therefore very time taking and difficult to determine which user-job mapping is the most relevant one for a given user, on the basis of their skills and interests. In order to serve consumers, we propose an information recommendation engine that utilises an algorithm to match a user's interests and abilities with available jobs. To form recommendations, the system uses different text filtration and similarity measures. Testing the model using data from a major job offering agencies shows that topic models are relevant and effective. Therefore, this technique can be applied to several other industries.