Personalized Product Recommendation in e-Commerce

Authors:
Sung-Shun Weng;Mei-Ju Liu
Affiliations:
-;-
Venue:
EEE '04 Proceedings of the 2004 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'04)
Year:
2004

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Abstract

The purpose of this paper is to analyze customers'purchasing behaviors based on product features fromtransaction records and product feature databases.Customers' preferences toward particular features ofproducts are analyzed and then rules of customerinterest profiles are thus derived in order torecommend customers products that have potentialattraction with customers. The approach of this paperhas its strength to be able to recommend to customersbrand new products or rarely purchased products aslong as they fit customer interest profiles. Thisresearch also derives customers' interest profiles thatcan explain recommendation results. The interests onparticular features of products can be referenced forproduct development.