Personality Prediction System to Improve Employee Recruitment

Personality is an important factor for predicting whether an applicant would be a perfect fit for the company. The personality of a candidate can give the recruiters an insight about the candidate and hence it can improve candidate selection. The fate of an organization depends on its employees, which makes the selection of the best candidate a very crucial matter for an organization. In the current scenario, the applicant will be selected for the particular job by going through his/her Curriculum Vitae (CV). But shortlisting and going through thousands of applicant CVs is a tedious and hectic task. Besides, one may not get a good idea about the personality of the candidate from a CV. The cost of bad hires can be saved if the recruiter selects the right candidate for a particular job role. Personality Prediction is finding out and comprehending the personality of an applicant which can be used in the present recruiting system. The personality of the candidate will not only help the recruiters in the selection but also provide the candidate with a good job role based on his personality. In this chapter, we have come up with a method to evaluate the personality of a candidate using different strategies. The proposed system asks CV-related and personality-based questions to predict and analyze his/her personality with the help of Machine Learning and Natural Language Processing which helps the organization to shortlist candidates based on the job profile and company requirements. Various Machine Learning Models were tested from which Logistic Regression provided the highest accuracy of 85.71%. Bidirectional Encoder Representations from Transformers or BERT is implemented to extract the keywords to provide recruiters an understanding about the candidate’s personality. Thus, the system will help the human resource to select the right candidate for the desired job profile, which in turn will provide an expert workforce for the organization.