电子商务中的一种潜在信任关系预测方法

Prediction of Latent Trust Relationships in E-commerce

信任关系在用户寻找可靠信息方面扮演了重要角色。已有信任关系预测方法主要基于信任的传递性和用户间的相似度。然而,在电子商务应用中,不同声誉度的用户对于商品的评价会对其他用户的购买行为产生不同的影响,用户声誉度的差异性会在较大程度上影响用户间建立信任关系的可能性。因此,针对电子商务应用,给出了用户信任关系子网络和用户商品评价关系子网络的形式化描述。根据社会学理论,提出了一种基于用户相似度和全局声誉度的潜在信任关系预测方法,旨在挖掘电子商务应用中陌生用户间潜在的信任与不信任关系,为用户辨别评价信息的可信性,进而选择可信商品提供辅助决策。基于Epinions数据集的对比实验结果表明,该方法在信任关系预测的准确度方面有较好的表现。

Trust relationships play an important role in helping users collect reliable information.Existing trust relationships prediction methods are mainly based on the trust transitivity and user similarity.However,in e-commerce systems,reviews from users with different reputations may have different impacts on other users＇ purchasing behaviors.Different user reputations may have different impacts on trust relationships prediction.Therefore,this paper formally described a user-trust relationships sub-network and a user-product-review relationships sub-network in e-commerce systems.According to sociological theory,a trust relationships prediction method was proposed based on user similarity and global reputation,which aims at discovering the latent trust relationships between unfamiliar users in e-commerce systems and helping users distinguish the reliability of rating information in order to choose reliable products.Comparative experiments on the trust relationships prediction were performed on Epinions dataset.The experimental results show that the proposed method has better trust prediction accuracy.