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Job opportunities recommendation for visually impaired people using natural language processing

Abdul Ghapar, Azimah and Azman, Feninferina and Ahmad Faudzi, Masyura and Baskaran, Hasventhran and Abdul Rahim, Fiza (2022) Job opportunities recommendation for visually impaired people using natural language processing. Journal of Theoretical and Applied Information Technology, 100 (2). pp. 543-553. ISSN 1992-8645

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Official URL: http://www.jatit.org/volumes/onehundred02.php


This paper highlights the importance of job recommendation system and its function in helping job seekers to find available job opportunities. As various efforts focusing on job recommendation systems for sighted people, this study aims to explore how Natural Language Processing (NLP) techniques can assist visually impaired people in finding the suitable job. In this paper, we propose a job recommendation model architecture that enables the job seekers to get the most suitable job match for their profile and also allows the employers to identify qualified individuals for specific job position. The solution is based on an NLP program that will be hosted through an Application Programming Interface (API) service and connected to the Web interface. A comprehensive procedure in the proposed architecture is divided into three layers: input layer, data processing layer, and output layer. The proposed solution is expected to help visually impaired people get the result for the job that matches their qualifications and experiences and also for the employer to find a suitable candidate for the advertised position.

Item Type:Article
Uncontrolled Keywords:candidate filtering, job matching, job recommendation, NLP, recommender systems
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Razak School of Engineering and Advanced Technology
ID Code:98580
Deposited By: Yanti Mohd Shah
Deposited On:21 Jan 2023 09:06
Last Modified:21 Jan 2023 09:06

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