Funding was provided by Natural Science Foundation of Hunan Province (CN) (Grant No. 2018JJ2023) and Scientific Research Fund of Hunan Provincial Education Department (Grant No. 17C0295).
机构署名：
本校为第一机构
院系归属：
信息与电子工程学院
摘要：
Traditional collaborative filtering recommendation algorithm has the problems of sparse data and limited user preference information. To deal with data sparseness problem and the unreliability phenomenon on the traditional social network recommendation. This paper presents a novel algorithm based on trust relationship reconstruction and social network delivery. This paper introduces the method of eliminating falsehood and storing truth to avoid the unreliable phenomenon and improves the accuracy of falsehood according to the user similarity for...
