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@article{179805,
        author = {Vivek M},
        title = {SMART ATS: Intelligent Resume Screening Using  Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {9217-9220},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179805},
        abstract = {This paper introduces SMART ATS, a machine learning-based system designed to automate resume screening. It uses natural language processing to extract and analyze key details from resumes, matching them with job descriptions to generate relevance scores. The system streamlines recruitment by reducing manual effort, improving candidate shortlisting, and promoting efficient, unbiased hiring.},
        keywords = {Applicant Tracking System (ATS), intelligent resume screening, machine learning, natural language processing (NLP), resume parsing, job-candidate matching, automated recruitment systems, candidate ranking, feature extraction, TF-IDF, support vector machines (SVM), Random Forest, Naive Bayes, bias mitigation in AI, ethical hiring, talent acquisition, recruitment analytics, semantic matching, artificial intelligence in human resources, resume classification.},
        month = {June},
        }