Goods Recommendation Sysrem using a Customer’s Preference Features Information

As electronic commerce systems have been widely used, the necessity of adaptive e-commerce agent systems has been increased. These kinds of adaptive e-commerce agents can monitor customer`s behaviors and cluster thou in similar categories, and include user`s preference from each category. In order to implement our adaptive e-commerce agent system, in this paper, we propose an adaptive e-commerce agent systems consider customer`s information of interest and goodwill ratio about preference goods. Proposed system build user`s profile more accurately to get adaptability for user`s behavior of buying and provide useful product information without inefficient searching based on such user`s profile. The proposed system composed with three parts , Monitor Agent which grasps user`s intension using monitoring, similarity reference Agent which refers to similar group of behavior pattern after teamed behavior pattern of user, Interest Analyzing Agent which personalized behavior DB as a change of user`s behavior.