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当前信任推理机制在建立移动社交网络用户之间的联系中起着关键的作用。本文描述了一个由用户的联系形成的隐社交行为图构建算法。通过对用户的联系关系进行评分排名,从而形成一个动态联系等级,帮助用户评估移动社交网络环境中的用户之间的信任值。通过联系、互动演变和用户属性的水平来计算基于分组的信任值,再通过基于不同分组的信任值的聚合来获得一个集群信任值,探讨了一个全范围的移动社交网络集群信任值的传递。证明了在移动社交网络的微博信息分享系统中的基于分组行为关系的有效性。
Current trust reasoning mechanisms play a key role in establishing the links between users of mobile social networks. This paper describes a hidden social behavior graph building algorithm formed by the user’s contact. Ranking users by their relationship to form a dynamic contact rating helps users to assess the value of trust among users in a mobile social networking environment. The trust value based on grouping is calculated by the level of association, interactive evolution and user attributes, and then the trust value of a cluster is obtained through the aggregation of trust values based on different groups. The trust value of a whole range of mobile social network clusters is discussed. It proves the validity of packet-based behavior in the microblog information sharing system of mobile social network.