Paper Contents
Abstract
Resume screening is the process of reviewing candidatesprofiles to find the most suitable person for a job role. Traditionally, this process is manual, time-consuming, and sometimes biased, especially when there are many applications. To overcome these challenges, we propose an AI-Powered Resume Analyzer that automates the resume screening process using machine learning and natural language processing (NLP) techniques. The system extracts and analyzes key information from resumes, such as skills, qualifications, and experience, and compares them with job requirements. Additionally, the system provides feedback to candidates, explaining why their resumes were not shortlisted based on specific factors, helping them improve their future applications. The tool also includes visualizations to display candidate rankings, making it easier for HR professionals to assess resumes. This solution reduces the time and effort involved in screening, ensures fair and unbiased evaluations, and enhances the overall recruitment process by offering valuable insights for decision-making. Keywords: Resume screening, Automated recruitment, Natural Language Processing (NLP), Machine Learning, Feedback System, Resume Visualization
Copyright
Copyright © 2025 Jaddu Jyothi. This is an open access article distributed under the Creative Commons Attribution License.
