Abstract: The recruitment process in today's competitive job market is often hindered by the inefficiencies of manual resume screening. The AI Resume Analyzer aims to streamline this process using Natural Language Processing (NLP) and machine learning techniques. This tool automates the extraction of critical information from resumes and provides real-time recommendations to both applicants and administrators. By leveraging advanced algorithms and a resume parser technique, the system categorizes and analyzes resumes based on job roles, extracting essential details like skills, experience, and education. The analyzer also offers practical recommendations for applicants, such as additional skills and certifications that could enhance their profiles, and provides practical resources for resume improvement. For administrators, the tool facilitates data management and analytics, allowing for comprehensive data downloads, the generation of visual reports, and the tracking of applicant trends. Implemented using Streamlit for the frontend and backend, MySQL for database management, and Python for data processing, the AI Resume Analyzer addresses the limitations of manual screening by offering a faster, more accurate, and consistent method of evaluating resumes. This system not only reduces the time and effort required for candidate evaluation but also ensures a more objective and efficient hiring process, ultimately aiding organizations in identifying the best candidates.
Keywords: Machine learning, Natural Language processing, recommendation.
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DOI:
10.17148/IJARCCE.2024.13905
