Predicting Suitable Careers Through Deep Belief Networks And Game Playing

Abstract

Deciding on a career path is a Major Decision in one's life. Many professionals suffer from poor performance in the career path they have chosen earlier in their lives. The industry is also suffering due to the wrong people being assigned the right jobs.  Generally, there is a relationship between a person's cognitive factors, which may change from time to time, and the kind of jobs they can perform efficiently. Skills acquired by a person directly correlate with the cognitive levels and the kind of jobs that a person can undertake. The selection of a proper career that matches the skills acquired dependent on the cognitive levels is the most critical issue that must be addressed by building cognitive, expert, and learning models. Assessing the cognitive levels of a person is complex, and predicting suitable careers based on the cognitive levels is further complicated due to the lack of proper expert models which can learn from a live example set. This paper presents a method that computes the psychological levels through game playing and uses the results to determine the skills acquired. Using the skills, the method predicts suitable careers that the students and professionals can effectively pursue. The learning of the expert model required is implemented through Deep Belief Networks. 98% Accuracy in the proper prediction of the careers has been achieved using the Cognitive, Expert and Learning models presented in the paper.