Abstract :

In The Modern Recruitment Process, Organizations Receive A Large Number Of Resumes For Every Job Posting, Making Manual Screening Time-consuming And Prone To Errors. This Project Presents A Resume Analyzer System Using Natural Language Processing (NLP) Techniques Implemented In Python. The System Automatically Parses And Extracts Essential Information From Resumes, Such As Personal Details, Educational Qualifications, Skills, Work Experience, And Certifications. Additionally, It Evaluates The Relevance Of A Candidate’s Profile Against Job Requirements Using Keyword Matching And Semantic Similarity Measures. By Leveraging NLP Libraries And Algorithms, The System Provides A Fast, Accurate, And Unbiased Assessment, Thereby Assisting HR Professionals In Efficient Candidate Shortlisting. The Proposed Solution Also Supports Ranking Of Candidates And Visualization Of Extracted Skills, Making The Recruitment Process More Streamlined And Data-driven. Keywords: Resume Analysis, Natural Language Processing (NLP), Python, Information Extraction, Candidate Screening, Keyword Matching, Semantic Similarity, Recruitment Automation, HR Analytics

Published:

28-10-2025

Issue:

Vol. 25 No. 10 (2025)

Page Nos:

206-211

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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