摘要：

在现有的电子商务交易信任算法中,多数忽视用户主观偏好的不确定性,且未考虑语言评价信息。为此,建立一种多维集成信息的信任模型。将多维信任反馈信息集成为区间直觉模糊数,基于逼近理想解排序法计算其相对于理想区间直觉模糊数的贴近度,并对各服务实体的信任程度进行排序。在模型中加入惩罚项,以防止网上欺诈行为。仿真结果表明,该模型考虑用户的主观风险偏好,能够对定量和定性评价信息进行有效评估,其防欺诈能力优于区间云模型。

关键词: 区间直觉模糊, 信任评价, 逼近理想解排序法, 模糊贴近度, 风险偏好

Abstract:

Most existing electronic commerce trust algorithms ignores the uncertainty of consumers’ subjective preference and dosn’t consider language evaluation information.To solve the problem,a multi-dimension integrated trust model is proposed.Multi-dimension trust feedback information is integrated into interval-valued intuitionistic fuzzy numbers.Based on Technique for Order Preference by Similarity to Ideal Solution (TOPSIS),the neartude between the interval-valued intuitionsic fuzzy numbers and the ideal intuitionsic fuzzy numbers is calculated,and the trust of service entities is ranked according to the neartude.To prevent the internet fraud,the penalty term is added into the model.The simulation results show that the decision-makers’ risk preference,the quantitative and qualitative evaluation information are taken into consideration in the model,and its anti-fraud ability is better than the interval-valued cloud model.

Key words: interval-valued intuitionstic fuzzy, trust evaluation, Technique for Order Preference by Similarity to Ideal Solution(TOPSIS), fuzzy neartude, risk preference

中图分类号: 

• TP393.092