ResuMatch: AI-Powered Resume-Job Description Matching System
Subhranshu Pathak ,Vishal Gupta, Aman Kumar, Vishwas Chakrawarti
Department of Computer Science and Engineering
KCC Institute of Technology and Management
Greater Noida, India
Email: namanpathak777@gmail.com
Email: hii.vishalgupta@gmail.com
Email: amanchakrawarti88@gmail.com
Email: vs206242@gmail.com
Dr. Mohd Sadim
Professor, Department of Computer Science and Engineering KCC Institute of Technology and Management
Greater Noida, India
Abstract—The goal of ResuMatch is to introduce a modern, fair, and intelligent recruitment support system that automates the process of mapping candidate resumes to job descriptions using advanced artificial intelligence techniques. The system focuses on improving hiring accuracy while reducing the man- ual screening effort typically performed by HR professionals. It leverages semantic text representation models, section-wise resume extraction logic, and weighted matching algorithms that compare skills, experience, and qualifications against role-specific requirements. Unlike traditional keyword-based screening, Re- suMatch performs contextual interpretation to identify relevant competencies even when presented using different wording styles.
A core emphasis of this work is on transparency, interpretabil- ity, and unbiased evaluation. The system produces structured match outputs, including similarity scores, critical skill gaps, and categorized strengths, supporting objective decision-making for recruiters. Furthermore, candidates benefit from improvement- oriented feedback, enabling them to refine their resumes and enhance eligibility for future opportunities. The implementation pipeline integrates automated text extraction, NLP-based normal- ization, vector embedding generation, scoring logic, and visual dashboards for HR users and academic placement cells.
ResuMatch includes robust preprocessing, domain-wise skill mapping, relevance weighting strategies, and evaluation of match- ing consistency across varied resume formats. The system is de- ployed through an interactive interface that displays section-wise match insights, missing technical areas, and role-fit recommenda- tions. By combining intelligent matching, transparency, and user- focused interpretability, ResuMatch offers a practical AI-based hiring framework that enhances decision reliability, reduces bias, and redefines modern resume-job alignment workflows.
Index Terms—AI resume matching, hiring automation, NLP, matching algorithm, skill extraction
