计算机工程2017，Vol.43Issue(8)：236-242,7.DOI:10.3969/j.issn.1000-3428.2017.08.040
融合信任传播和奇异值分解的社会化推荐算法
Social Recommendation Algorithm Integrating Trust Propagation and Singular Value Decomposition
摘要
Abstract
Aiming at the data sparsity of user trust matrix,this paper designs a propagation rule for trust relationships among users.It computes the trust degree of user according to the rule,and then uses the trust degree to fill the user trust matrix.It proposes a social recommendation algorithm based on users' trust propagation algorithm and Singular Value Decomposition(SVD)model,The user scoring matrix is combined with the trust relation matrix to improve The prediction accuracy of the recommended system.Experimental results on both Epinions and Filmtrust publicly available datasets show that compared with the traditional recommendation algorithm,the proposed algorithm has higher recommendation quality.关键词
推荐系统/社会化推荐/信任网络/信任传播/奇异值分解Key words
recommendation system/social recommendation/trust network/trust propagation/Singular Value Decomposition(SVD)分类
信息技术与安全科学引用本文复制引用
李卫疆,齐静,余正涛,赵铁军..融合信任传播和奇异值分解的社会化推荐算法[J].计算机工程,2017,43(8):236-242,7.基金项目
国家自然科学基金(61363045) （61363045）
科技部科技创新人才基金(2014HE001) （2014HE001）
云南省自然科学基金重点项目(2013FA130). （2013FA130）
