Information Technology Resume Analyzer and Career Field Recommender

Authors

  • Dr. Sunil Bhutada  Head of Department, Information Technology Department, Sreenidhi Institute of Science and Technology, Yamnampet, Hyderabad, India
  • Mohd. Shamsh Uddin  Bachelor of Technology, IT Department, Sreenidhi Institute of Science and Technology, Yamnampet, Hyderabad, India
  • Savanth Dhatrika  Bachelor of Technology, IT Department, Sreenidhi Institute of Science and Technology, Yamnampet, Hyderabad, India
  • Shakir Bashir  Bachelor of Technology, IT Department, Sreenidhi Institute of Science and Technology, Yamnampet, Hyderabad, India

Keywords:

Resume Analysis, Career Field Recommendation, Skills Extraction, Personal Details Extraction, Natural Language Processing.

Abstract

Almost all recruiters in the field of Information Technology have to go through a large number of resumes every time they need to hire a person(s) for a job in the market. Going through the data present in each and every resume to shortlist candidates can be a difficult task. The project objectives are to extract details from a person’s resume and analyze them. This application uses few Natural Language Processing techniques to parse through data in a resume and use this parsed data to evaluate certain features that generally exists in any resume of a person in the field of Information Technology. Skills are the most important feature of a resume when it comes to the field of Information Technology. A person’s career field is recommended based on the skills extracted from the resume of the person. Further analysis of all the resumes are done by storing them along with their scores and recommended career fields to make the shortlisting process easy for the recruiter(here admin).

References

Downloads

Published

2022-06-30

Issue

Section

Research Articles

How to Cite

[1]
Dr. Sunil Bhutada, Mohd. Shamsh Uddin, Savanth Dhatrika, Shakir Bashir, " Information Technology Resume Analyzer and Career Field Recommender, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 9, Issue 3, pp.354-359, May-June-2022.