Hybrid recommendation based on forgetting curve and domain nearest neighbor
Li Zhou · Guanli kexue xuebao · 2012
Content-based filtering and collaborative filtering are the two most classical algorithms in recommendation system.However,there is the new customer problem in content filtering which does not consider the influences of users' interests drifting on recommendation quality.And collaborative filtering faces severe challenges of data sparisity and cold start.To solve these problems,a hybrid recommendation algorithm is proposed in this paper.First,the paper builds a Customer Interests Model(CIM) based on the Forgetting Curve to predict the unevaluated rating;then introduces the processing method of domain nearest neighbor to find the nearest neighbors for target users to predict the unevaluated rating;and finally,makes the recommendation.The experimental results show that the proposed method can improve the recommendation quality effectively.