Citation

Haw, Su Cheng and Chew, Lit Jie and Ong, Kyle and Ng, Kok Why and Naveen, Palanichamy and Anaam, Elham Abdulwahab (2022) Content-based Recommender System with Descriptive Analytics. Journal of System and Management Sciences, 12 (5). pp. 105-120. ISSN 1816-6075, 1818-0523

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Abstract

A recommendation system (RS) is an information filtering system that provides users with information, which one may be interested in. Ontology modelling has been widely used to conceptualize items and their semantic relationship together. Hence, in this paper, we propose an intelligent CB RS that allows users to not only access the product recommendations, but also the dashboard systems, which contain descriptive analytics, modeled using ontology. The dashboard allows users to have insight into past data. It consists of five main features: (i) Highlight Dashboard, (ii) Customer Dashboard, (iii) Advanced Search, (iv) Pivot Table and Pivot Chart, and (v) Report. Experimental evaluations show that the CB RS can return the accurate recommended product in a real propriety dataset.

Item Type:	Article
Uncontrolled Keywords:	content-based, recommender system, recommender technique, ontology, e-commerce.
Subjects:	H Social Sciences > HF Commerce > HF5001-6182 Business > HF5546-5548.6 Office management > HF5548.32-.34 Electronic commerce
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	01 Dec 2022 03:39
Last Modified:	01 Dec 2022 03:39
URII:	http://shdl.mmu.edu.my/id/eprint/10877

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