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Bimonthly Since 1986 |
ISSN 1004-9037
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Publication Details |
Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
Distributed by:
China: All Local Post Offices
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Abstract
A disabled person is large minority groups, mostly ignored by society and gets deprived from employment. Finding work is the most difficult task for those with impairments. The job opportunities for people with disabilities are limited at present due to their physical disabilities. This leads to poverty that affects the basic quality of their life and stability. This paper proposes a job recommendation system for people with disabilities based on a qualitative approach. This system will classify the disabled people based on their disabilities using c5.0 algorithm and it will recommend the jobs available for them. Dealing with the large amount of recruiting information on the Internet, a disabled job seeker always spends many hours to find the useful information. The proposed system uses hybrid recommendation by combining collaborative filtering with content-based recommendation based on the candidate profile to predict the best suitable job for them. The system estimates up to minimum 85% of accuracy in recommending of jobs.
Keyword
Hybrid Recommendation, Collaborative Filtering, C5.0 algorithm, Content-Based Recommendation.
PDF Download (click here)
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