Collaborative filtering recommendation model based on semantic Web and user trust network
XU Shou-ku · Jisuanji yingyong yanjiu · 2014
Collaborative filtering is hard to find similar users due to suffering from data sparsity,cold-start problems,resulting in the problem of recommendation accuracy and reliability to some extend.Based on ontology and semantic Web,this paper aimed to alleviate these problems in terms of finding more similar users by automatically building trust network and computing trust weights between users.At last,an example validated the remarkable effects of this approach.