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JRDP: A Job Recommender System Based on Ontology for Disabled People
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Author(s): Saman Shishehchi (Department of Electrical and Computer Engineering, Buein Zahra Technical University, Buein Zahra, Iran)and Seyed Yashar Banihashem (Department of Electrical and Computer Engineering, Buein Zahra Technical University, Buein Zahra, Iran)
Copyright: 2019
Volume: 15
Issue: 1
Pages: 15
Source title:
International Journal of Technology and Human Interaction (IJTHI)
Editor(s)-in-Chief: Anabela Mesquita (ISCAP/IPP and Algoritmi Centre, University of Minho, Portugal)and Chia-Wen Tsai (Ming Chuan University, Taiwan)
DOI: 10.4018/IJTHI.2019010106
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Abstract
Despite the high number of people with disabilities, there are only a few job recommender systems that cater to their needs. This study analyses the implementation of an ontology based recommender system (JRDP) that offers suitable jobs to the disabled. The system considers whether or not an assistive technology exists to address certain disabilities in a specific application domain. If so, a list of available jobs from the application domain would be recommended to the disabled workforces. Two modules are considered as main components of the framework; knowledge-based and recommendation modules. 10 applicant with various disabilities participated in the testing session. The T-test evaluation demonstrates that JRDP requires less time for the recommendation process compared to ontology-less recommendation systems. The mean values for each construct of questionnaire can be calculated using the usability test, with the average mean reported to be 4.55. Cronbach's Alpha was used for testing the reliability of questionnaire, reporting a value of (0.759), which confirms its reliability.
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