RESUME JOB MATCHER USING COSINE SIMILARITY

Abstract

The Resume Job Matcher uses NLP and cosine similarity to compare resumes with job descriptions. It cleans and processes text using tokenization, stop-word removal, and TF-IDF vectorization to turn it into numerical form. This helps find how closely a candidate’s skills match the job needs. Unlike simple keyword matching, it understands the meaning of words for better results. The system saves time in screening, improves hiring accuracy, and gives fair results. It can also work with web apps and databases, making it useful for real hiring situations. Overall, it makes the recruitment process smarter and more efficient. The project shows how AI can simplify hiring by matching the right candidates faster. It provides a reliable and scalable solution for modern recruitment platforms.