Developing a Technique to Select Potential Candidates Using a Combination of Rough Sets and Fuzzy Sets

Abstract

Every company often needs to recruit efficient people for the betterment of the company. Human Resource (HR) department of a company plays main role in recruitment process of employees. In this recruitment process, in most of the cases they ask the job seekers to submit their resumes via online. In general, many applicants submit their resumes for jobs. Manual analysis of these resumes for obtaining potential candidates for the organization is very time consuming and inefficient. Considering this fact, in this paper, we propose a potential candidate selection approach using a combination of rough and fuzzy sets. Our system considers all resumes under consideration and extracts necessary information such as skills, department, CGPA, experience etc. from each resume. After extracting necessary information from the resumes, the system applies dimension reduction technique using the concepts of rough set. Our system then clusters the information using fuzzy c-means clustering algorithm. Finally, the system generates outputs based on the priority of the job requirements from that clustered information. We have conducted several experiments to show the effectiveness of our approach. From our experimental evaluation, we can say that our approach can recommend potential candidates efficiently.