摘要： 由于大数据环境下个体行为具有多样性的特点,使得基于局部信息的一般个体行为信任评价模型考虑因素不全面,导致个体面临信任危机。为此,提出一种改进的个体行为信任评价模型。采用多数据融合获得信任评价结果,利用D-S理论对关联信任评价的个体信任mass函数值与评估结果进行整合,计算个体出现不信任情况的概率。融合个体信任态势求出关联个体的不信任态势,获得个体参与信任评价的权重,得出个体行为信任评价。实验结果表明,与基于局部信息的一般个体行为信任评价模型相比,该模型具有更高的可靠性和安全性。

关键词: 大数据, 社交网络, 信任评价, 个体行为, 信任态势

Abstract: Because the individual behavior has diversity characteristics under the big data environment,it results that the consideration of the general individual behavior trust evaluation model based on local information is not comprehensive,causing serious trust crisis of individual.Therefor,this paper presents an improved trust evaluation model of individual behavior.Firstly,it uses multi-data fusion to get the result of trust evaluation,and then fuses the mass function of the individual trust of relative trust evaluation and the evaluation results by using the theory of D-S.It gets the probability of the individual appearing distrust.Each related individual distrust situation is obtained by the fusion with individual trust situation factor,and it can get the fusion of weight about each individual participating in the individual behavior trust evaluation and the individual behavior trust evaluation.Experimental result shows the proposed model has higher reliability and security than the general trust evaluation model based on local information.

Key words: big data, social network, trust evaluation, individual behavior, trust situation

中图分类号: 

• TP393