Performance analysis of machine learning algorithms in resume recommendation systems

Abstract

We present an evaluation of machine learning algorithms on a model prepared by us for improving the recruitment processes of organizations. The recruitment of candidates, being an important process for any organization, entails the hiring of employees that would be best fit for the job and ultimately beneficial for them. We have taken resumes of candidates of an organization and extracted the attributes (namely academics, qualifications, etc. to name a few) and assessed them according to a scale and a corresponding scoring system to train our system so that the candidates with the best scores can be shortlisted. We applied algorithms like decision tree, support vector machine, multi-linear regression and Bayesian ridge regression to train our system. Of all these the best results were given by decision tree and support vector machine regression.