Machine Learning Based Resume Recommendation System

Authors

  • Anushka Lad UG Scholar, Department of Electronics and Telecommunication Engineering, K. C. College of Engineering and Management Studies and Research, Thane, India
  • Siddhi Ghosalkar UG Scholar, Department of Electronics and Telecommunication Engineering, K. C. College of Engineering and Management Studies and Research, Thane, India
  • Balkrishna Bane UG Scholar, Department of Electronics and Telecommunication Engineering, K. C. College of Engineering and Management Studies and Research, Thane, India
  • Krutika Pagade UG Scholar, Department of Electronics and Telecommunication Engineering, K. C. College of Engineering and Management Studies and Research, Thane, India
  • Anupama Chaurasia Assistant Professor, Department of Electronics and Telecommunication Engineering, K. C. College of Engineering and Management Studies and Research, Thane, India

Keywords:

K-NN, Machine Learning, NLP

Abstract

Filtering resumes out of bulk is more difficult and time intense task for recruiters. Since corporations received resume in immense quantity and typically it usually has tangential and unnecessary data. With the assistance of machine learning, a correct and quicker system are often created which might save days for recruiters to scan every resume manually. KNN Algorithm is used to classify the resumes according to their respective categories. Our model can facilitate the recruiters to scan the resume based on the requirements they have entered. Basic workflow is that the recruiters upload a job description and bunch of resumes received to the tool. It ranks resumes on the basis of job description given.

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Published

03-05-2022

Issue

Section

Articles

How to Cite

[1]
A. Lad, S. Ghosalkar, B. Bane, K. Pagade, and A. Chaurasia, “Machine Learning Based Resume Recommendation System”, IJMDES, vol. 1, no. 3, pp. 17–20, May 2022, Accessed: Jul. 22, 2024. [Online]. Available: https://journal.ijmdes.com/ijmdes/article/view/17

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