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@article{204263,
        author = {Shruthika.C and Dr.S.Radha and Ms.C.Visali and Mrs.T.janani},
        title = {RESUME SCREENING SYSTEM USING NLP &MACHINE LEARNING TECHNIQUES},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {2302-2308},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=204263},
        abstract = {The initiative “Resume Screening System using NLP & Machine Learning Techniques” aims to create an intelligent system that automates the assessment of resumes and recommends the best job positions for the applicants. In traditional recruiting approaches, a Recruiter must assess resumes manually through screening, which is time-consuming, subject to human bias, and inefficient where there are a large number of applicants. This system leverages machine learning (ML) and natural language processing (NLP) techniques to extract and interpret relevant information presented in resumes such as skill, education, experience, and achievements. The relevant facts are collected, compared with job descriptions stored in a database, and aligned to facilitate the selection of the best job matches. The system utilizes similarity algorithms and ranking algorithms to quantify and determine the degree of a candidate's relevance to the job position. By building an automated approach, screening can happen in a more efficient manner, allowing Recruiters to spend more time on interviewing and selecting candidates. Additionally, candidates gain from the system through personalized recommendations for jobs that are aligned with their credentials and preferences. Moreover, candidates and Recruitment stakeholders can feel assured that the evaluation does not have bias or human subjectiveness, as the evaluation was determined solely from data. This is a significant advancement toward better recruiting accuracy, improving decisions, and placing the best candidates with the best opportunities.},
        keywords = {Human Activity Recognition, Smartphone Sensors, Machine Learning, Health Recommendation System},
        month = {June},
        }