In online social network,trust is the basis of reliable interaction between users,and the strengths of interaction al-so affect trust establishment.Although many researchers have studied approaches of trust model and prediction,most trust modeling methods are based on the existing trust network,and lack the in-depth study of user interaction and contents.This paper studied the sparseness of the original network and the effect of user’s interaction behavior.Therefore,it presented a no-vel trust prediction framework based on both a trust network and the interactive contexts between users and put forward a kind of measurement mechanism to evaluate the strength of interaction relations.Combined with the existing trust network,learned and used a trust prediction threshold value to predict unknown trust relations.Empirical experiments conductes on Epinions dataset show that the unknown trust relations can be effectively predicted combining with the user’s interaction behaviors,and the user’s interaction behaviors can improve the performance of the trust prediction model.%在线社会网络中，信任关系是用户间进行可靠交互的基础，交互的强度也会影响用户间信任关系的建立。虽然许多研究者对信任建模及其预测进行了研究，但大部分的研究都是基于已有网络进行的，缺乏对用户交互行为及内容的深入研究。在这种情况下，针对原有网络的稀疏性问题和用户交互行为对信任关系的影响进行了研究，提出了一种基于信任网络和用户评分行为的信任预测框架。该框架给出了一种评估用户间交互关系强弱的度量机制，结合用户间已建立的信任关系网络，综合评估预测用户间的信任与不信任关系。基于Epinions网站的真实数据集进行了多组实验，实验表明用户交互行为对信任的度量有着重要的影响，综合考虑这两方面可以更准确地对信任关系作出预测。
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