摘要
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。
Nowadays the trust inference mechanism has played a key role in establishing links between mobile social net-work users. This paper describes an implicit social behavior graph construction algorithm formed by the user＇s association.By ranking users＇ associations, a dynamic link level is created to help users evaluate the trust value among users in a mo-bile social network environment. Then, the group trust value is calculated based on the level of contact, interaction and userattributes. After that, obtains a cluster trust value by aggregation of the trust value based on different groups, and discussesthe transfer of trust value of a full-scale mobile social network clusters. Finally, it proved the effectiveness of the pack-et-based behavioral relation in the micro-blog information sharing system of the mobile social network.
出处
《情报科学》
CSSCI
北大核心
2016年第11期129-134,共6页
Information Science
基金
国家自然科学基金面上项目(71573073)
湖北省自然科学基金项目(2015CFB303)
湖北省科技厅软科学项目(2015BDF090)
湖北省教育厅哲学社会科学研究重大项目(15JD023)
关键词
隐社交行为图
移动社交网络
集群组的信任
pictures of implicit social network
mobile social network
trust of cluster groups
