一种动态信任度量与预测方法研究  

Research of a Dynamic Trust Measurement and Prediction Method

作　　者：赵茜[1] 王新生[1] 

机构地区：[1]燕山大学信息科学与工程学院,河北秦皇岛066004

出　　处：《计算机工程与科学》2010年第9期20-22,共3页Computer Engineering & Science

摘　　要：开放系统中的信任关系本质上是最复杂的社会关系之一,涉及假设、期望、行为和环境多种因子,很难准确地定量表示和预测。本文在现有的基于行为监控的动态信任模型的基础上,把粗糙集理论和信息熵理论结合起来应用于信任度量与预测模块。通过实验证明,新的条件信息熵权重确定方法可以解决原有权重确定方法自适应性差和行为数据规模的扩展能力差的问题。In an open system,trust is one of the most complex concepts in social relationships,involving many decision factors,such as assumptions,expectations and behaviors,etc. So,it is very difficult to quantify and forecast accurately. Combined with rough set and information entropy,a new dynamic trust forecasting model is proposed.Experiments show that the new method of weight determined by conditional information entrophy can solve the problems of the bad self-adaptation and the poor data scale expansion ability brought by the original weight determination.

关 键 词：动态信任预测模型 分类知识 粗糙集 信息熵 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]