Dynamic radius for context- aware recommender system

Alawadhi, Nayef and Taha Alshaikhli, Imad Fakhri and Alkandari, Abdulrahman (2021) Dynamic radius for context- aware recommender system. Journal of Engineering Science and Technology, Special Issue (5). pp. 57-65. ISSN 1823-4690

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Abstract

In the field of transportation and smart cities, context-aware recommendation is a trending subject that targets users’ satisfaction and comfort. The subject has developed from e-commerce to cover different domains including path planning at urban areas. Researchers were competed in delivering the level of contribution in many areas. Search radius is considered a major pillar at any context-aware recommender framework, however, in many studies the search radius is not having a major contribution in the delivered systems. In this paper, a dynamic search radius algorithm is introduced as part of a context-aware recommender framework. Agglomerations and competition effects are used to enhance search radius results. Deep neural network is a major artificial intelligence method used in this research to tackle cold-start problem and to improve recommendation outcomes.

Item Type:	Article (Journal)
Uncontrolled Keywords:	Agglomeration effect, Context-aware recommender, Competition effect, Deep neural network, Proximity, Radius.
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User:	Professor Imad Taha
Date Deposited:	23 Nov 2021 08:28
Last Modified:	23 Nov 2021 08:28
URI:	http://irep.iium.edu.my/id/eprint/93999

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