计算机与数字工程2025，Vol.53Issue(3)：652-659,8.DOI:10.3969/j.issn.1672-9722.2025.03.008
基于用户潜在信任与被信任关系的推荐系统
Recommender Systems Based on User Latent Trust and Trusted Relationship
摘要
Abstract
The existed recommender system models are relatively conservative due to the dramatic increase in the number of users and entries,and the potential correlation information between users without full consideration.As such,this paper proposes a novel model of recommender systems based on that utilizes the latent trust and trusted relationship between users.Specifically,the model has the following characteristics.The matrix of potential trust and trusted relationship between users can be obtained by intro-ducing the graph Laplacian regularization to ensure the user structure information in the latent trust space.The consistency of similar users'preferences for scoring items is ensured via knowledge transfer of the obtained relationship matrix to the decomposition pro-cess of the scoring matrix as well as the utilization of the locally learned social regulation of similar users,and the computational complexity caused by knowledge transfer is effectively reduced by resorting to a new single-factor-based variable update principle.Finally,the experimental results on six real datasets show that the model proposed in this paper can achieve high prediction accura-cy while ensuring computational efficiency.关键词
推荐系统/潜在信任关系/潜在被信任关系/图拉普拉斯正则化Key words
recommender system/latent trust relationship/latent trusted relationship/graph Laplacian regularization分类
信息技术与安全科学引用本文复制引用
于佳玄,李明,丁德锐..基于用户潜在信任与被信任关系的推荐系统[J].计算机与数字工程,2025,53(3):652-659,8.基金项目
国家自然科学基金项目(编号:61973219)资助. （编号:61973219）
