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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM54900

AI-Driven Job Matching and Interview Automation System

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM54900

Volume:

9 |

12 |

Dec 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM54900

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

HPG

Hema Prabha G

RU

Rohith U

SG

Sadhana G

YKE

Yashvanth Kumar E

SS

Santhosh S

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Abstract

The AI-Driven Job Matching and Interview Automation System is an intelligent platform designed to revolutionize the recruitment process by leveraging artificial intelligence and automation technologies. The system uses advanced machine learning algorithms and natural language processing (NLP) techniques to analyze candidate resumes, assess skill sets, and match them with the most suitable job opportunities based on qualifications, experience, and preferences. Additionally, the platform automates the initial interview process using AI-powered virtual interviewers that evaluate candidates through real-time question-and-answer sessions, facial and speech analysis, and performance scoring. This approach minimizes human bias, reduces manual workload for recruiters, and speeds up the hiring cycle while ensuring a fair and data-driven evaluation of candidates. The proposed system not only enhances efficiency and accuracy in recruitment but also provides a seamless and interactive experience for both employers and job seekers, paving the way for a smarter and more effective hiring ecosystem.

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Cite This Article

Hema Prabha G, Rohith U, Sadhana G, Yashvanth Kumar E, Santhosh S, "AI-Driven Job Matching and Interview Automation System," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 12, Dec 2025. https://doi.org/10.55041/IJSREM54900

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9/11/2025

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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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