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@article{171767,
        author = {Reethu K and Sandeep S Naik and Anvitha G Rao and Kripa K and Krithi K},
        title = {Intelligent Resume Analysis And Job Fit Assessment System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {8},
        pages = {921-926},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=171767},
        abstract = {The "Intelligent Resume Analysis and Job Fit Assessment System" presents an opportunity to improve and automate the recruitment process through intelligent methods of resume analysis and evaluating job compatibility. Given the huge number of job applicants exponentially increasing, companies have encountered inefficiency in handling manually sifted resumes. We propose a system that uses Machine Learning and Natural Language Processing techniques to automate resume parsing and assess job fit. The system will use TF-IDF to extract meaningful keywords from resumes and job descriptions, and K-Nearest Neighbours to match resumes with the most suitable job roles based on the alignment of skills and experience. Moreover, Cosine Similarity is used in the measurement of similarity of resume and job description with which the prediction of job fit gets even more accurate.},
        keywords = {resume, machine learning, NLP, KNN, cosine similarity, feedback.},
        month = {January},
        }