International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | To Implement an Intelligent Job Portal Analytics and Recommendation System Using Machine Learning |
|---|---|
| ABSTRACT | The Smart Job Portal Analytics and Recommendation System is designed to enhance the traditional job search process using Artificial Intelligence and Machine Learning techniques. The system provides intelligent features such as resume evaluation, salary prediction, skill gap analysis, and personalized job recommendations. It analyzes user profiles and job market data to offer data-driven insights that improve employability. The platform also includes city-wise demand analysis and an AI chatbot for real-time interaction. This system bridges the gap between job seekers and recruiters by providing accurate, efficient, and personalized solutions, making the recruitment process faster and more effective.. |
| AUTHOR | NISHANTHI. A, ARTHI J, KUMARI A, SHIVANI T Assistant Professor, Department of Computer Science and Engineering, P.S.V College of Engineering and Technology, Mittapalli, Krishnagiri, India. UG Scholar, Department of Computer Science and Engineering, P.S.V College of Engineering and Technology, Mittapalli, Krishnagiri, India |
| VOLUME | 183 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1404044 |
| pdf/44_To Implement an Intelligent Job Portal Analytics and Recommendation System Using Machine Learning.pdf | |
| KEYWORDS | |
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