AI-Powered Job Search: A Centralized and Personalized Employment Matching System
AI-Powered Job Search: A Centralized and Personalized Employment Matching System
Authors:
Shreyash Bapaurao Aware
Neha Dilip Shirvankar
Department of Computer Science
Dr. D.Y. Patil Arts, Commerce and Science College, Pimpri
Abstract
Job seekers today face the challenge of navigating multiple recruitment portals, often wasting time on repetitive searches and receiving irrelevant suggestions. This inefficiency largely stems from keyword-based matching, which fails to capture the deeper meaning of resumes and job postings.
We propose a unified platform that applies Artificial Intelligence (AI), Natural Language Processing (NLP), and Machine Learning (ML) to deliver context-aware recommendations. The system aggregates listings from diverse sources, interprets resumes through semantic analysis, and compares them with job descriptions using meaning-based similarity rather than word overlap. Additionally, it highlights missing skills and provides tailored improvement advice. The result is a faster, more accurate, and personalised job search experience.
Keywords:
AI, NLP, Machine Learning, Resume Analysis, Semantic Matching, Skill Gap Detection