Smart Resume Analyzer: An Automated Approach for Recruitment Process

This work presents an automated Resume Analyzer system to streamline the initial resume screening process. Designed to alleviate recruiters’ workloads, the system extracts key resume details—such as name, contact information, experience, and qualifications—without manual input. This system leverages Natural Language Processing (NLP) and text mining. A novel scoring mechanism evaluates resumes based on the presence of essential elements like declarations, interests, and skill sets. This web tool provides a resume score which is used by organization and applicants to review about it. This tool allows recruiters to assess resumes in PDF with a rating rapidly, saving them both time and effort. The SVM algorithm outperformed kNN, Naïve Bayes, Decision Tree and Random Forest.