基于用户间动态信任关系的推荐算法研究  

Recommender Algorithm Based on Dynamical Trust Relationship between Users

作　　者：郑炅[1] 石刚[1,2] 

机构地区：[1]新疆大学信息科学与工程学院,乌鲁木齐830046 [2]清华大学计算机科学与技术系,北京100084

出　　处：《计算机科学》2015年第9期230-234,共5页Computer Science

基　　金：新疆维吾尔自治区高校科研启动基金(XJEDU2011S06)资助

摘　　要：在电子商务中,用户对商品的决策很大程度上取决于用户间的社会信任关系。传统的推荐算法往往考虑用户间的静态关系,即决策依赖的社会关系图是不变的。实际上,用户对好友的信任度往往随着时间的变化而变化。为了描述动态的信任关系在推荐系统中的作用,提出了一种基于动态信任关系的推荐算法。首先,提出了一种考虑用户的静态兴趣和静态信任关系的产生式模型;然后,分别将时序因素加入到用户兴趣和信任关系的描述,并提出了相应的动态产生式模型。实验表明,提出的算法能很好地描述用户之间信任关系随时间的变化,并且与其它相关算法相比,评价值的预测准确性得到了明显的提高。In e-commerce,a user＇s selection of item largely depends on the trust relationship of users. Traditional re- commender algorithms usually consider the static relationship between users, that is, the depended relationship for deci- sion is changeless. In order to describe the importance of static trust relationship in recommender system, this paper proposed a dynamical trust relationship based recommender algorithm. First, we proposed a generative model that takes both static user inte-rest and static trust relationship into consideration. Then, we added temporal factor into user inte- rest and trust relationship, and proposed corresponding dynamical generative model. The experiments show that the pro- posed algorithm can describe the dynamical trust relationship between users, and has better prediction accuracy than re- lated algorithms.

关 键 词：电子商务 推荐系统 信任关系 协同过滤 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]