The existing approaches to predict trust values in social commerce are based on personal social relationships without considering historical transaction information about products in social commerce, which results in false recommendations, and deceptions cannot be differentiated. Trust values extracted from social links can improve the performance of trust and reputation mechanism, but the rates from these links in social commerce can be false because of the stakeholders’ manipulation for personal interest. And the rates are also dynamic and inconsistent. Therefore, this paper proposes a comprehensive trust model by fully exploiting the effects of the transaction attributes and social relationships on users’ trust. The proposed model refines the granularity of trust evaluation and improves the discrimination of recommended information. Experiments demonstrate that the proposed model performs better and predicts more accurately than the three models compared under the same circumstance.

中文翻译：

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基于社会关系和交易属性的综合信任模型

现有的在社交商务中预测信任值的方法是基于个人社交关系，而没有考虑有关社交商务中产品的历史交易信息，这会导致错误的建议，并且欺骗性也无法区分。从社交链接中提取的信任值可以改善信任和声誉机制的性能，但是由于利益相关者为个人利益而进行的操纵，在社交商务中从这些链接中获取的信任率可能是错误的。而且费率也是动态的和不一致的。因此，本文通过充分利用交易属性和社会关系对用户信任的影响，提出了一种综合信任模型。提出的模型改进了信任评估的粒度，并改善了对推荐信息的区分。