Automated Resume Classification Using Machine Learning

  • Pradeep Kumar Roy
  • , Sunil Kumar Singh
  • , Tapan Kumar Das*
  • , Asis Kumar Tripathy
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

One of the current job recruiter’s biggest challenges is to filter the right candidate’s resume over the pool of resumes. For a single job post, many times more than thousands of applicants send their resumes. However, many of them are not suitable for the offered job. Manually filtering the right candidate’s resume is not feasible from the pool; hence, an automated system may help pick the selective candidate’s resume by applying natural language processing. This research suggested a machine learning-based automated resume classification model which classifies the resume into different categories based on their content. The experiment is done with the dataset consisting of ten categories of resumes. The outcomes of the proposed model achieve satisfactory classification reports in terms of precision, recall and F1-score with bi-gram model.

Original languageEnglish
Title of host publicationAdvances in Distributed Computing and Machine Learning - Proceedings of ICADCML 2022
EditorsRashmi Ranjan Rout, Soumya Kanti Ghosh, Prasanta K. Jana, Asis Kumar Tripathy, Jyoti Prakash Sahoo, Kuan-Ching Li
PublisherSpringer Science and Business Media Deutschland GmbH
Pages307-316
Number of pages10
ISBN (Print)9789811910173
DOIs
Publication statusPublished - 2022
Event3rd International Conference on Advances in Distributed Computing and Machine Learning, ICADCML 2022 - Warangal, India
Duration: 15-01-202216-01-2022

Publication series

NameLecture Notes in Networks and Systems
Volume427
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference3rd International Conference on Advances in Distributed Computing and Machine Learning, ICADCML 2022
Country/TerritoryIndia
CityWarangal
Period15-01-2216-01-22

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications

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