Authors : Mrunali Wande; Dr. Manisha Bharati

Volume/Issue : Volume 11 - 2026, Issue 5 - May

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Google Scholar : https://tinyurl.com/5n89uc6u

Scribd : https://tinyurl.com/wntt8bvz

DOI : https://doi.org/10.38124/ijisrt/26May1118

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

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Abstract : However, modern recruitment process suffers from delays because of manual, inconsistent and biased analysis of numerous resumes. In this study, we propose to create a Smart Resume Analysis and Ranking System, which will be an advanced intelligent recruitment assistant designed as a four-tab Streamlit web application with multi-modal input/output interface. Our system includes Natural Language Processing (NLP) techniques and Machine Learning (ML)The system consists of several modules:(i) A single-resume analysis module that:- evaluates how well ATS-compatible a given resume is with a weighted formula including four components.

Keywords : Resume Analysis, ATS Score, NLP, XGBoost, SBERT, Skill Gap Detection, HALA Algorithm, Voice Resume, Candidate Ranking, Streamlit, TheFuzz, Knowledge Graph, TF-IDF, Machine Learning.

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