What does this research mean for the field?

An intelligent, Django-based college placement management platform featuring an AI-based matching engine automates and streamlines the campus recruitment process, reducing manual effort and improving coordination. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

The aim is to improve campus placement efficiency by automating the recruitment process.

April 23, 2026Open Access

Intelligent College Placement Management Platform

Key Points

The aim is to improve campus placement efficiency by automating the recruitment process.
Developed as a full-stack web application using Django framework.
Employs a simulated AI-based matching engine for job and student profile alignment.
Supports roles for students, recruiters, and placement officers.
Increased efficiency by reducing manual tasks associated with placement management.
Enhanced decision-making through AI-generated match scores.
Provided real-time insights into placement activities for better coordination.

Abstract

Campus placement plays a vital role in connecting engineering students with employers, but many institutions still rely on manual methods such as spreadsheets and emails, leading to inefficiencies. The Intelligent College Placement Management Platform is a full-stack web application developed using the Django framework to automate and streamline the entire placement process.The system supports three user roles: students, recruiters, and placement officers. Students can create profiles, upload resumes, apply for jobs, and track application status. Recruiters can post job openings, review applications, and issue offer letters. Placement officers manage the system through a centralized dashboard that provides real-time insights into placement activities.A key feature of the platform is the simulated AI-based matching engine, which uses natural language processing techniques to compare student skills with job requirements and generate a match score. This improves decision-making for both students and recruiters.The system also enforces placement policies such as the One-Student-One-Offer rule.Built using Python, Django, SQLite, and Bootstrap, the platform ensures efficient, transparent, and scalable placement management, improving coordination and reducing manual effort in campus recruitment processes.

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