An adaptive trust prediction framework for diverse data model

摘要：

　　The trust relationship is gaining importance in addressing information overload and personalized recommendation in rating based social networks.Current trust prediction models have significant drawbacks and limitations,particularly in terms of handling the diversity of user interactions.In this paper,we extract the features of trust relationship and classify trust metrics.Proposing a universality framework through comparing and qualitative analyze the existing prediction model.With this framework,we avoid the problem of the web of trust sparsity and solve the limitations of current methods when faced with diverse data models.

关键词： Trust prediction Social networks Dataset

作者: Lin Yang Tiejian Luo

作者单位: University of Chinese Academy of Sciences,Beijing,China

会议类型: 国际会议

会议名称: The 9th International Conference on Pervasive Computing and Application(ICPCA 2014)(第九届全国普适计算学术会议、第九届全国人机交互联合学术会议)

会议地点: 南昌

会议语种:英文

页码: 1-10

在线出版日期: 2013-09-26（万方平台首次上网日期，不代表论文的发表时间）