A Community-Based Collaborative Filtering System Dealing with Sparsity Problem and Data Imperfections

摘要

In this paper, we develop a collaborative filtering system for not only tackling the sparsity problem by exploiting community context information but for also dealing with data imperfections by means of Dempster-Shafer theory. The experimental results show that the proposed system achieves better performance when comparing it with a similar system, CoFiDS.