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RezFind: NLP-Based Resume Shortlisting
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Author(s): Srikanth K. (Woxsen University, India), Dibya Nandan Mishra (Woxsen University, India), Pratyusha Pujari (Woxsen University, India), Pingili Sravya (Woxsen University, India), Vishal K. (Woxsen University, India)and Sankalp Chenna (Woxsen University, India)
Copyright: 2023
Pages: 11
Source title:
Handbook of Research on AI and Knowledge Engineering for Real-Time Business Intelligence
Source Author(s)/Editor(s): Kamal Kant Hiran (Sir Padampat Singhania University, India & Lincoln University College, Malaysia), K. Hemachandran (Woxsen University, India), Anil Pise (University of the Witwatersrand, South Africa)and B. Justus Rabi (Christian College of Engineering and Technology, India)
DOI: 10.4018/978-1-6684-6519-6.ch019
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Abstract
A typical job posting on any job-hunting portal like Linkedin, Naukri, Indeed, etc., will receive many resumes. Screening a resume manually is a tedious process involving huge costs. Screening resumes also consumes a lot of time for the hiring managers. Sometimes, because of the massive numbers, a few qualified resumes don't get noticed, leading to considerable loss to both the company and a loss of opportunity for the applicant. This study uses advanced natural language processing to automate the resume screening process. It also describes a data mining method to extract relevant information like the eligible applicant's name, contact, and email. RezFind provides a unique scoring system that gives a similarity score between the job description and the resume to keep it very specific to the job posting instead of a generic screening. This process allows keeping the uniqueness of each job role, and the screening quality increases by having a specific job description.
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