Intelligent Resume Parsing and Job Recommendation via Web-Based CV Analysis System

The process of matching job applicants to suitable job openings is typically inefficient due to unorganized resume formats and absence of customized job search facilities. This paper presents a light-weight web-based system that automatically extracts structured information from PDF resumes and recommends suitable job openings based on publicly available job search APIs. The system is based on natural language processing-based data extraction, stores the extracted information in a CSV database, and builds context-sensitive job queries. A basic web interface built on top of Flask supports PDF uploads and displays results in real-time. Our prototype is efficient for small to medium-sized datasets and recommends future work on incorporating intelligent ranking and resume optimization.