Resume Analyzer Using NLP to Match JOB Description

Abstract

In the changing world of recruitment, organizations must efficiently sift through large numbers of resumes to find candidates that fit specific job roles. This paper introduces a web-based Resume Analyzer System that uses Natural Language Processing (NLP) and machine learning to automate resume evaluation and job matching. The system includes two main modules: Admin (HR/Recruiter) and Job Seeker. The admin module allows recruiters to post jobs, manage candidate applications, and view ranked resumes based on similarity scores. The Job Seeker module enables applicants to register, upload resumes in PDF or DOCX formats, explore job openings, and apply directly through the platform. Using NLP, the system extracts key features such as skills, work experience, and educational background from resumes and job descriptions. A machine learning-based matching algorithm calculates a similarity index to evaluate candidate suitability and highlights missing or recommended skills. Additionally, the platform classifies resumes into relevant categories, assesses document quality, and integrates with online professional profiles. By reducing manual work and bias in the screening process, the proposed Resume Analyzer improves accuracy, fairness, and efficiency in recruitment, benefiting both recruiters and job applicants.