A WEB-BASED RECRUITMENT PLATFORM INTEGRATING MACHINE LEARNING FOR PERSONALITY PREDICTION

Abstract: The Personality Prediction System is a web-based recruitment platform that leverages machine learning to enhance the hiring process by predicting candidate personalities and recommending suitable job roles. Developed using ASP.NET for the frontend, the system incorporates a Gradient Boosting Machine (GBM) model to analyze responses from a multiple-choice personality test and generate predictions. The platform is structured into three main modules: Admin, Company, and Candidate. Admins can manage and communicate with both companies and candidates, view test results, and oversee system activity. Companies can create and manage job vacancies, initiate personality assessments for applicants, and view the resulting predictions to aid in selection. Candidates can update their profiles, generate resumes using ASP.NET Web API and iTextSharp, take personality tests when requested by companies, and receive tailored job recommendations based on their predicted personality type. The system includes a messaging feature across all modules for effective communication, making it a comprehensive, intelligent, and user-friendly solution for modern recruitment.

Keywords: Personality Prediction, Recruitment System, Machine Learning, Gradient Boosting Machine, Job Recommendation