A personalized recommendation model based on the user-state awareness
Teng Ji, Pan Tuo-Yu, Zhu Zhenmin, Lu Kai · 2009
Major recommendation systems don't consider the user's current composite state in time. And also they do not consider the affect on the recommendation results when the user updates the context. In the process of analyzing the user's interests and preferences, it is not enough to determine the user state only based on the browsing records about the user, so more context information from the user's current activity is need excavated. In this paper, a personalized recommendation model based on the user-state awareness is proposed. Through the complement of the user-state perception, the recommendation system is more intelligent and has a higher service quality.