유비쿼터스 환경에서 연관규칙과 협업필터링을 이용한 상품그룹추천

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

  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.