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@article{202860,
        author = {Bodakhe Sanket Eknath and Sul Tanish Bhagwat and Gajanan santosh Kshisager and Rushikesh Nagesh Bhaskare and Sachin. D. Pandhare},
        title = {NLP-Based Intelligent Resume Screening System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {12167-12170},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=202860},
        abstract = {This research paper presents an NLP-Based Intelligent Resume Screening System that uses Artificial Intelligence, Natural Language Processing (NLP), and Machine Learning (ML) to automate and improve the recruitment process. The system analyzes resumes by extracting important information such as skills, education, work experience, and certifications, and then compares these details with job requirements to identify suitable candidates. The proposed approach helps reduce manual effort, saves screening time, and improves the accuracy of candidate selection while supporting fair and consistent hiring decisions. In addition, the system provides resume scoring and recommendations that assist applicants in improving their resumes according to industry needs. The study highlights how AI-driven recruitment technology can enhance hiring efficiency and provide a smarter and more reliable talent acquisition process.},
        keywords = {},
        month = {May},
        }