AI-Powered Resume Analyzer and Job Matching System: A Comprehensive Review

Authors

Harsh Saxena

Data Science (CSE)Shri Ramswaroop Memorial College of Engineering and Management (AKTU) Lucknow (India)

Geetanshu

Data Science (CSE)Shri Ramswaroop Memorial College of Engineering and Management (AKTU) Lucknow (India)

Ayodhya Prasad

Artificial intellignce & Data science Shri Ramswaroop Memorial College of Engineering and Management (AKTU) Lucknow (India)

Samiksha Singh

Computer Science & EngineeringShri Ramswaroop Memorial College of Engineering and Management (AKTU) Lucknow (India)

Article Information

DOI: 10.51584/IJRIAS.2025.101100036

Subject Category: Artificial Intelligence

Volume/Issue: 10/11 | Page No: 382-387

Publication Timeline

Submitted: 2025-11-14

Accepted: 2025-11-26

Published: 2025-12-08

Abstract

The AI-based job recommendation system employs Natural Language Processing (NLP), Large Language Models (LLMs), and API-based job search to automate and optimize career matching. Technical skills, experience, and job keywords are extracted from resumes with Spacy NLP and regex-based text analysis to allow candidate profiling. Information is processed with Ollama Mistral, a high-performance LLM, to predict the best job role to match based on skills and industry standards. Real- time job recommendations are obtained with RapidAPI's Job Search API, with the ability to filter search results with location-based filtering. The system optimizes job search efficiency, minimizes manual effort, and improves job-to- candidate matching accuracy. Skill gap analysis, AI-driven job ranking, and professional profile integration (Linked-In, GitHub) can be added to future development for improving recommendations. This project demonstrates the revolutionary capability of AI in employment matching, making job searching intelligent, data-driven, and personalized.

Keywords

Natural Language Processing (NLP), Large Language

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