ISSN No:2250-3676 ----- Crossref DOI Prefix: 10.64771
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Scholarly Peer Reviewed and Fully Referred Open Access Multidisciplinary Monthly Research Journal


    SMARTHIRE: AI-DRIVEN RESUME SCREENING SYSTEM

    Ms.Sarla Sunitha,N.Kavya,Nusharath,P.Himavarshini

    Author

    ID: 1857

    DOI: Https://doi.org/10.64771/ijesat.2025.v25.i12.pp109-115

    Abstract :

    SmartHire: AI-Driven Resume Screening System Is Designed To Automate And Enhance The Recruitment Process By Leveraging Artificial Intelligence To Evaluate Resumes With Improved Accuracy, Speed, And Fairness. Traditional Manual Screening Is Time-consuming, Prone To Human Bias, And Inefficient When Dealing With Large Applicant Pools. SmartHire Addresses These Challenges Through A Combination Of Natural Language Processing (NLP), Machine Learning (ML), And Rule-based Filtering Techniques To Extract Key Candidate Attributes, Analyze Skills, Match Job Requirements, And Generate Suitability Scores. The System Intelligently Detects Relevant Experience, Educational Qualifications, Domainspecific Competencies, And Soft-skill Indicators From Unstructured Resume Data. Additionally, SmartHire Prioritizes Transparency By Providing Recruiters With Explainable Ranking Outcomes And Eliminating Repetitive Manual Tasks. The Result Is A Scalable, Consistent, And Data-driven Screening Solution That Significantly Reduces Hiring Time And Improves The Quality Of Shortlisted Candidates. Keywords: Resume Screening, Natural Language Processing (NLP), Machine Learning (ML), Recruitment Automation, Skill Extraction, Candidate Ranking, Explainable AI, Talent Matching, AI-driven Hiring, Automated Recruitment Systems.

    Published:

    11-12-2025

    Issue:

    Vol. 25 No. 12 (2025)


    Page Nos:

    109-115


    Section:

    Articles

    License:

    This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

    How to Cite

    Ms.Sarla Sunitha,N.Kavya,Nusharath,P.Himavarshini, SMARTHIRE: AI-DRIVEN RESUME SCREENING SYSTEM , 2025, International Journal of Engineering Sciences and Advanced Technology, 25(12), Page 109-115, ISSN No: 2250-3676.

    DOI: https://doi.org/10.64771/ijesat.2025.v25.i12.pp109-115