Optimizing Applicant Tracking Systems using N...

Optimizing Applicant Tracking Systems using Natural Language Processing: A Data-Driven Approach to Resume Analysis

Author Name : Ankit Goswami, Akshdeep Gurjar, Isha Agrawal, Dr. Rajdeep Chakraborty, Sachin Yele

ABSTRACT This research paper presents a 7000-word investigation into NLP-powered Applicant Tracking Systems (ATS), addressing critical challenges in automated resume screening. The study evaluates 8 machine learning architectures across 4 realworld resume datasets containing 12,000+ documents, proposing a novel hybrid NLP pipeline that achieves 94.2% accuracy in skill-job matching.