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Product-group Recommendation based on Association Rule Mining and Collaborative Filtering in Ubiquitous Computing Environment  

Kim, Jae-Kyeong (경희대학교 경영대학)
Oh, Hee-Young (경희대학교 경영대학)
Kwon, Oh-Byung (경희대학교 국제경영학부)
Publication Information
Journal of Information Technology Services / v.6, no.2, 2007 , pp. 113-123 More about this Journal
Abstract
In ubiquitous computing environment such as ubiquitous marketplace (u-market), there is a need of providing context-based personalization service while considering the nomadic user preference and corresponding requirements. To do so, the recommendation systems should deal with the tremendous amount of context data. Hence, the purpose of this paper is to propose a novel recommendation method which provides the products-group list of the customers in u-market based on the shopping intention and preferences. We have developed FREPIRS(FREquent Purchased Item-sets Recommendation Service), which makes recommendation listof product-group, not individual product. Collaborative filtering and apriori algorithm are adopted in FREPIRS to build product-group.
Keywords
U-market; Product-group Recommendation; Collaborative Filtering; Apriori algorithm;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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