International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 6 November-December 2024 Submit your research before last 3 days of December to publish your research paper in the issue of November-December.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 6 Issue 6
November-December 2024

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

NLP-Powered Resume Matching For Recruitment

Author(s) Isha Rathi, Pooja Kolaskar, Lavina Tangralu, Manisha Mali
Country India
Abstract More recently, recruitment has largely relied on the automation of the matching process between candidates and job roles. In this regard, this paper focuses on the development of a resume parser application utilizing NLP techniques, PDF text extraction, and machine learning-based evaluation of resumes according to job descriptions. In developing the application using the Flask framework, users are allowed to upload resume and job description files in PDF format. The system automatically extracts the text, preprocesses it, and performs the task of skill matching. It also computes a semantic similarity score based on term frequency-inverse document frequency and cosine similarity techniques. Using a trained machine learning model, the application predicts a binary job fit score based on its semantic similarity and skills matching metrics scores. This paper outlines the design, implementation, and evaluation of the system, and it indeed has the potential to assist the recruiters in pre-screening the candidates.
Keywords Resume Parsing, Natural Language Processing (NLP), Automation, Candidate Screening, Resume Matching, Job Description, Applicant Tracking System, Semantic Similarity.
Field Engineering
Published In Volume 6, Issue 6, November-December 2024
Published On 2024-11-29
Cite This NLP-Powered Resume Matching For Recruitment - Isha Rathi, Pooja Kolaskar, Lavina Tangralu, Manisha Mali - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.31742
DOI https://doi.org/10.36948/ijfmr.2024.v06i06.31742
Short DOI https://doi.org/g8sg6q
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 6 Isu 6Cover Page Vol 6 Isu 5Cover Page Vol 6 Isu 4

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9898-5948-55 editor@ijfmr.com