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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM52715
Volume:
9 |
9 |
Sep 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The recruitment process is often hindered by inefficiencies such as time-intensive manual resume screening, duplicate candidate submissions, and the absence of a centralized tracking mechanism. These challenges not only delay hiring decisions but also impact the accuracy and consistency of candidate evaluation. This project presents an AI-powered recruitment tool designed to address these issues by integrating two core modules: a Resume Evaluator and an Applicant Tracking System (ATS). The Resume Evaluator allows users to upload a job description (JD) along with up to ten resumes simultaneously. Using natural language processing and semantic similarity algorithms, it ranks resume based on relevance to the JD. Users can customize evaluation criteria such as skills, experience, and
KEYWORDS
Publication Date
9/21/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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