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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM19287

Recruitment Using Machine Learning

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM19287

Volume:

7 |

4 |

Apr 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

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

MN

Mihir Narkar

JT

Jatin Tiwari

SA

Sahil Ambavale

PP

Purva Pawar

DT

Dr.Divya Tamma

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Abstract

The aim of this project is to develop an online recruitment portal for the employer and the job aspirant. The System we have designed is a website which has a user login and an employer login. The project has been organised to solve the problem in the existing system where in the existing system includes conventional procedures which are deliberate and difficult. Now that internet is available to all , job aspirants respond on the online job portals it makes the job search systematic and well organised for the aspirant. It assits the recruiter find the talent they need and also assists the job aspirants to find current vacancies at one place. In addition to this, a course page is also provided on the portal where in if an applicant lacks certain skill set that is required by the organization , then he can take a course for that and when completed can apply again for the organization. The proposed system uses word cloud to fetch skills from the resume of the applicant and matches it with the skills required by the employer for the job. From candidate hiring to job listing various features have been provided on the portal.

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Cite This Article

Mihir Narkar, Jatin Tiwari, Sahil Ambavale, Purva Pawar, Dr.Divya Tamma, "Recruitment Using Machine Learning," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 4, Apr 2023.

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Publication Date

4/20/2023

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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