中文摘要：

向用户提供更多的积极、个性化的服务的一种关键启用技术是的服务建议机制在活动聚会的重要研究话题之一联网(MSN ) 。同时， MSN 产生匿名的信息或黑客行动的各种各样的类型。信任能减少和未知实体的相互作用的风险并且阻止恶意的攻击。在我们的论文，我们在场在当计算目标用户的可靠邻居时，认为用户是类似和朋友熟悉的 MSN 的一个基于信任的服务建议算法。第一，我们使用上下文信息和共同评估的项目的数字定义用户类似。然后，由空间的六度的理论激发了，朋友熟悉被基于图的方法导出。因此，建议方法被在建议阶段认为用户是上下文进一步提高。最后，一套模拟被进行评估算法的精确性。结果证明朋友熟悉和用户类似罐头有效地改进熟悉多于用户类似贡献的建议表演，和朋友。

英文摘要：

The service recommendation mechanism as a key enabling technology that provides users with more proactive and personalized service is one of the important research topics in mobile social network （MSN）. Meanwhile, MSN is susceptible to various types of anonymous information or hacker actions. Trust can reduce the risk of interaction with unknown entities and prevent malicious attacks. In our paper, we present a trust-based service recommendation algorithm in MSN that considers users＇ similarity and friends＇ familiarity when computing trustworthy neighbors of target users. Firstly, we use the context information and the number of co-rated items to define users＇ similarity. Then, motivated by the theory of six degrees of space, the friend familiarity is derived by graph-based method. Thus the proposed methods are further enhanced by considering users＇ context in the recommendation phase. Finally, a set of simulations are conducted to evaluate the accuracy of the algorithm. The results show that the friend familiarity and user similarity can effectively improve the recommendation performance, and the friend familiarity contributes more than the user similarity.