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@article{205405,
        author = {Satish Laxman Datar and Rohit Shivaji Rathod and Nachiket Ratan Shrikhande},
        title = {AI Resume Analyzer: A Smart NLP-Powered Resume Analysis and Career Recommendation System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {6640-6647},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=205405},
        abstract = {The AI Resume Analyzer is an intelligent web application developed using Python and Streamlit that automates the process of resume analysis, career field prediction, and skill recommendation. The system leverages Natural Language Processing (NLP) techniques to parse PDF resumes, extract key information such as skills, experience level, and contact details, and then generates actionable recommendations including missing skills, relevant courses, interview questions, and LinkedIn profile suggestions.
The application features a dual-panel architecture comprising a User Module for real-time resume feedback and an Admin Module for analytics and user management. An integrated ATS (Applicant Tracking System) Score Checker evaluates keyword compatibility against job descriptions, while a Cover Letter generation module and a multi-dimensional feedback system further enhance the platform's utility. The system stores all user interaction data in a MySQL database and presents visual analytics via Plotly charts. This paper discusses the system design, modules, implementation details, complete source code architecture, and future enhancement opportunities.},
        keywords = {Resume Analysis, NLP, ATS Score, Streamlit, Career Recommendation, Skill Extraction, Python, Machine Learning Portfolio},
        month = {June},
        }