PlaceMentor: An Intelligent Analytical Platform for College Placements

Abstract— The digitization of campus recruitment and placement systems is reshaping how educational institutions manage hiring processes. This research presents PlaceMentor, a Django-based analytical platform built to streamline and enhance college placement activities using data-driven techniques and modern web technologies. The platform enables administrators and placement officers to manage historical placement data, forecast recruitment trends using regression analysis, and extract in-demand skills through text processing. Notable features include resume parsing, clustering of students based on skill similarity, and company-student matchmaking using similarity measures. The system offers secure user authentication with role-based access and dynamic dashboards for real- time visualization. With tools for generating downloadable reports and automating recommendations, PlaceMentor improves efficiency, transparency, and decision-making in campus placement operations. The study highlights how data analytics and system automation can modernize traditional placement processes in academic institutions. Keywords- Campus placements, Django, student clustering, recruitment forecasting, resume parsing, placement analytics, skill matching, data-driven decision making, educational automation.