Enhancing Recruitment Efficiency through an AI-Powered Personality Assessment Web Portal

Swapnil Gawande

Title:
Enhancing Recruitment Efficiency through an AI-Powered Personality Assessment Web Portal

Authors:
Swapnil Gawande

Cite This Article :

Swapnil Gawande "Enhancing Recruitment Efficiency through an AI-Powered Personality Assessment Web Portal" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Advancements and Emerging Trends in Computer Applications - Innovations, Challenges, and Future Prospects, March 2025, pp.1275-1279, URL: https://www.ijtsrd.com/papers/ijtsrd79826.pdf

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Abstract :
Traditional recruitment processes often face challenges in efficiently and objectively evaluating candidate personality traits, which are crucial predictors of job performance and organizational fit. This research presents the development and potential impact of an AI-powered web portal designed to streamline and enhance candidate personality assessment. The portal integrates advanced AI algorithms, including Natural Language Processing (NLP) and potentially machine learning models, to analyze textual and potentially other forms of candidate data (e.g., responses to open-ended questions, video interviews) and generate comprehensive personality profiles. This study details the system architecture, key functionalities, and the methodology employed in developing the AI models for personality trait extraction and prediction.

Keywords :
AI algorithms, Natural Language Processing (NLP), web portal, recruitment, machine learning

Publication Details:

Unique Identification Number : IJTSRD79826

Published In : Special Issue | Advancements and Emerging Trends in Computer Applications - Innovations, Challenges, and Future Prospects, March 2025

Page Number(s) : 1275-1279

Publisher Name : IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470

Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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