Citation

Haw, Su Cheng and Subramaniam, Samini and Chew, Lit Jie (2020) Recommender System for Retail Domain: An Insight on Techniques and Evaluations. ACM International Conference Proceeding Series. pp. 9-13. ISSN 2374-6769

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Abstract

Recommender system has been developed as a useful tool especially when we reached the era of big data and in the meanwhile the internet has been overwhelming with lots of choices. There is a need for people to filter the information to search for their needs and wants efficiently. E-commerce website such as Amazon and Netflix have been using recommender system to build and boost their sales through the personalization recommendation. With the success in the e-commerce area, researchers are keen on finding a method to boost traditional offline retailer sales thru the recommender system. Therefore, in this paper, we introduced the existing recommender system and discuss the method of filtering of each method. Then, we provide the overview of the recent paper in retailer and e-commerce domain to provide the insight and trends such as the filtering techniques and evaluation metric used. Several possible research direction has been discussed based on the current trends and problems.

Item Type:	Article
Uncontrolled Keywords:	Recommender system
Subjects:	Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	04 Jan 2022 00:48
Last Modified:	04 Jan 2022 00:48
URII:	http://shdl.mmu.edu.my/id/eprint/8298

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