GenAI-Powered ATS: Enhancing Recruitment with Skill Fitment Analysis

This study introduces a novel candidate-job matching framework leveraging Generative AI (GenAI) as an alternative to conventional Natural Language Processing (NLP) techniques. While existing research predominantly focuses on NLP-based resume parsing and keyword matching, our methodology utilizes GenAI to produce comprehensive skill assessments by evaluating candidate qualifications against job descriptions. The framework extracts candidate profiles from CVs and analyses their alignment with job requirements, classifying proficiency levels into four tiers: Beginner, Intermediate, Competent, or Expert. This GenAI-driven approach not only demonstrates higher matching accuracy compared to traditional methods but also provides actionable insights for both candidates and hiring managers, thereby streamlining recruitment workflows.

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Publication Details

Journal
International Research Journal on Advanced Engineering Hub (IRJAEH)
Published
2025-03-28
DOI
https://doi.org/10.47392/irjaeh.2025.0159
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

GenAI-Powered ATS: Enhancing Recruitment with Skill Fitment Analysis

Janhavi Patil, Sanjay Chaudhary, Krishna R. Kolekar, Samarth V. Zamre et al.
International Research Journal on Advanced Engineering Hub (IRJAEH)
Intelligent Tutoring Systems and Adaptive Learning
article

GenAI-Powered ATS: Enhancing Recruitment with Skill Fitment Analysis

Janhavi Patil, Sanjay Chaudhary, Krishna R. Kolekar, Samarth V. Zamre, Aniket S. Galzalwar
article en

Abstract

This study introduces a novel candidate-job matching framework leveraging Generative AI (GenAI) as an alternative to conventional Natural Language Processing (NLP) techniques. While existing research predominantly focuses on NLP-based resume parsing and keyword matching, our methodology utilizes GenAI to produce comprehensive skill assessments by evaluating candidate qualifications against job descriptions. The framework extracts candidate profiles from CVs and analyses their alignment with job requirements, classifying proficiency levels into four tiers: Beginner, Intermediate, Competent, or Expert. This GenAI-driven approach not only demonstrates higher matching accuracy compared to traditional methods but also provides actionable insights for both candidates and hiring managers, thereby streamlining recruitment workflows.

International Research Journal on Advanced Engineering Hub (IRJAEH)Vol. 3(03)
Maharaja Engineering College (IN)
Openalex Percentile: Top 96%
Intelligent Tutoring Systems and Adaptive Learning
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