CBR filtering algorithm and intelligent information recommending system
XI Junhong · Journal of Tsinghua University(Science and Technology) · 2006
Intelligent information recommending systems can kick out user-useless information using filtering algorithms and user's profile.This paper describes the architecture of an intelligent information recommending system which contains three functional levels,data level,filtering level,and result expressing level.A CBR(case-based reasoning) filtering algorithm was designed.The use's evaluations to the documents were defined as cases.Euclidean distance was used to compute the users' similarity.Finally experiments were made on a common data set using different filtering algorithms.The recall values were compared and analyzed.The results show that the CBR can improve the excitability of the collaborative filtering system.