Abstract :

The Intelligent Resume Evaluation And Candidate Shortlisting System Using AI Is Designed To Automate The Recruitment Screening Process By Intelligently Analyzing Applicant Resumes And Identifying The Most Suitable Candidates For A Given Job Role. The System Leverages Natural Language Processing (NLP), Machine Learning Algorithms, And Semantic Matching Techniques To Extract Key Information Such As Skills, Qualifications, Experience, And Achievements From Unstructured Resume Data. It Then Compares These Features With Predefined Job Requirements To Generate A Relevance Score For Each Applicant. The Approach Reduces Manual Effort, Minimizes Human Bias, And Enhances The Accuracy And Consistency Of Candidate Selection. The System Provides Recruiters With A Prioritized Shortlist, Supporting Faster Decision-making And Improving Overall Hiring Efficiency. By Integrating Real-time Analytics And Adaptive Learning, The Model Continuously Refines Its Screening Performance Based On Recruiter Feedback. This AI-driven Solution Aims To Streamline The Recruitment Workflow, Improve Talent Acquisition Quality, And Support Organizations In Selecting The Best-fit Candidates Effectively And Transparently. Keywords: AI-based Resume Screening, Candidate Shortlisting, Natural Language Processing (NLP), Machine Learning, Automated Hiring System, Skill Matching, Recruitment Analytics, Talent Acquisition Optimization.

Published:

11-12-2025

Issue:

Vol. 25 No. 12 (2025)

Page Nos:

151-156

Section:

Articles

License:

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

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