Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
@article{200493,
author = {Uday Amol Gore and Sahas Umesh Bhosale and Ayush Gagan Chinchkar and Suraj Nana Gadadare and Omkar Dattatray Narute},
title = {AI Enhanced Campus Recruitment Portal},
journal = {International Journal of Innovative Research in Technology},
year = {2026},
volume = {12},
number = {12},
pages = {1735-1740},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=200493},
abstract = {Campus recruitment plays a crucial role in connecting graduating students with employment opportunities. However, the traditional placement process faces numerous challenges such as manual data management, slow communication between students and companies, inefficient profile shortlisting, and limited real-time insights. These issues often result in delayed decision-making, mismatched candidate selection, and increased workload for Training & Placement (T&P) officers. The emergence of Artificial Intelligence (AI), Machine Learning, and Natural Language Processing (NLP) provides a transformative solution that enhances automation, improves accuracy, and enables intelligent decision support. This paper explores an AI-powered Campus Recruitment Portal that integrates modern web technologies with smart features including resume parsing, automated candidate shortlisting, job-role matching, chatbot assistance, and analytics dashboards. The system also leverages NLP to process natural language queries such as “Show eligible students for Software Engineer role,” or “Send notifications to shortlisted candidates. The proposed portal demonstrates how AI can streamline recruitment workflows, enhance efficiency for colleges and companies, and create a transparent, data-driven placement ecosystem. The integration of AI significantly reduces manual workload, enhances accuracy in applicant selection, and ensures a transparent, data-driven recruitment ecosystem. The proposed system demonstrates how AI-driven automation can modernize the entire campus hiring workflow.},
keywords = {AI Recruitement, Resume Parsing, NLP},
month = {May},
}
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