Published Paper Details:

This paper presents the design and implementation of an AI-based Resume Analyzer and Job Description Matcher system that automates candidate evaluation by comparing resumes with job requirements. The system leverages Natural Language Processing (NLP) and Machine Learning (ML) techniques to extract relevant information such as skills, experience, and education from resumes and match them against job descriptions. The proposed system calculates a match score, highlights missing skills, and provides improvement suggestions. The solution uses tools such as Python, spaCy, TF-IDF, and cosine similarity, along with optional Large Language Models (LLMs) for intelligent feedback. Experimental results show improved efficiency in recruitment processes and accurate candidate-job matching. The system reduces manual screening effort and enhances decision-making. Index Terms -- Resume Analysis, NLP, Machine Learning, Job Matching, TF-IDF, Cosine Similarity, AI Recruitment