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@article{187921,
        author = {Pravin Agarwal and Aaditi Tibhe and Amit Sharma},
        title = {Resume Analyzer Using NLP},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {7343-7349},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=187921},
        abstract = {Smart Resume Analyzer is a clever resume analysis job matching tool that improves your resumes automatically by dynamic scoring of your resumes and evaluating the job descriptions with your work experience. Applying NLP and machine learning algorithms, the system rapidly extracts, processes, and structures resume information with recruiter bias and manual parsing of resumes operating in the background. The system supports functionality and features like text extraction from PDF, named entity recognition, skill identification, and resume categorization to domains. We tested the system with a sample dataset of four resumes across four different domains: Data Science, Web Development, Android Development, and UI/UX Design. The results showed an accuracy of 92.4% in correctly classifying domains and 87.6% in extracting precise skills from resumes, indicating the system's effectiveness at generating actionable insights. We integrate an easy-to-use web-based interface for recruiters and candidates to effectively participate in the recruitment process and facilitate candidate-job matching through the Smart Resume Analyzer. We contribute to the recruitment process, skills development, application of machine learning for screening resumes and recommendations, as well as a transparent and open-source designed software system.},
        keywords = {Resume Analysis, Natural Language Processing, Skill Recommendation, Machine Learning, Automated Screening, Recruitment Technology.},
        month = {November},
        }