计算机应用研究2018，Vol.35Issue(1)：116-120,5.DOI:10.3969/j.issn.1001-3695.2018.01.024
采用信任网络增强的协同过滤算法
Enhanced collaborative filtering algorithm adopting trust network
李熠晨 1陈莉 1石晨晨 1兰小艳1
作者信息
- 1. 西北大学信息科学与技术学院,西安710127
- 折叠
摘要
Abstract
Due to the widespread data sparsity,traditional collaborative filtering system with single similarity cannot recommend accountably,meanwhile,the sparsity of co-rated items can lead to poor recommendation performance.In view of the above problems,this paper came into consideration an enhanced collaborative filtering algorithm adopting trust network (referred as ECFATN).This algorithm built a users' trust network based on the original user-item rating matrix by introducing the common trust relations of social network,established trust relationships between users with trust computation,and deliveried trust-relations with propagation rules.Then it linearly weighed trust and similarity between users to get a new weight.Finally a new recommendation way came out with this new weight.Experimental results show that this algorithm moderately alleviates data sparsity,and improves recommendation accuracy.Also,with the introduction of trust relations,this algorithm can improve user's cold-start problem.关键词
数据稀疏性/协同过滤/相似度/信任网络/用户冷启动Key words
data sparsity/collaborative filtering/similarity/trust-network/user's cold-start分类
信息技术与安全科学引用本文复制引用
李熠晨,陈莉,石晨晨,兰小艳..采用信任网络增强的协同过滤算法[J].计算机应用研究,2018,35(1):116-120,5.
