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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM28653

Machine Learning and NLP Based Resume Parsing Framework For E-Recruitment

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM28653

Volume:

8 |

2 |

Feb 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM28653

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

SN

Snehal Nikam

PP

Prathmesh Patil

SP

Supriya Pingale

YR

Yashaswini Rajebhosale

PKBD

Prof. K. B. Dhomse

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Abstract

The growth of the Indian recruitment market has led to the emergence of specialized recruitment agencies that leverage machine learning models to streamline the recruitment process and deliver the right talent to their clients. So, the proposed model has the potential benefits of the ML model to modify the hiring process and make it more efficient and fairer. By using NLP approaches, you can extract valuable information from resumes and provide accurate ratings based on the requirements of the company. With careful testing and refinement, your web portal could be a valuable resource for both job applicants and hiring managers alike. In addition, you could consider incorporating features such as personalized feedback and suggestions for improvement in the resume. This can help applicants to understand where they may be falling short and how they can improve their chances of being hired.

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Cite This Article

Snehal Nikam, Prathmesh Patil, Supriya Pingale, Yashaswini Rajebhosale, Prof. K. B. Dhomse, "Machine Learning and NLP Based Resume Parsing Framework For E-Recruitment," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 2, Feb 2024. https://doi.org/10.55041/IJSREM28653

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12/31/45427

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