AI-Based Resume Ranking System Using TF-IDF and Similarity Matching

AI-Based Resume Ranking System Using TF-IDF and Similarity Matching

Afrin Shaikh1

1Department of B.Voc Artificial Intelligence and Data Science,
AIARKP Abdul Razzaq Polytechnic, New Panvel

Abstract
This research explores the implementation of an AI-based resume ranking system using TF-IDF (Term Frequency-Inverse Document Frequency) for similarity scoring between resumes and job descriptions. The proposed model allows uploading of resume and job description files, extracts the text content, applies natural language processing (NLP) techniques such as tokenization and stopword removal, and then ranks the resume on a scale of 1–10 based on textual similarity. This method provides a lightweight, interpretable solution for HR departments to streamline candidate screening without complex black-box models.

Key Words: AI, Resume Screening, TF-IDF, Natural Language Processing, FastAPI, Candidate Ranking.