社会网络环境下基于分布式信任的在线评价方法

在线评价是社会网络环境下的一种新型多属性群决策问题.首先,为处理在线评价过程的不确定性,定义了分布式信任的运算法则、集成算子和排序方法等;其次,提出一种分布式信任社会网络分析方法,用来分析专家间的信任关系,并计算出每位专家的信任权重;再次,基于在线评价信息,结合最大和最小平均加权距离来综合确定未知的属性权重,并利用相对贴近度对备选方案进行排序,进而提出一种基于分布式信任的扩展TOPSIS法;最后,通过实例分析表明所提出方法的可行性.

A distributed trust based online evaluation under social network

Online review is a new type of multi-attribute group decision making problem under the social network environment. Firstly, in order to deal with the uncertainty of online evaluation process, the paper defines the algorithms of distributed trust, the integration operator and the sorting method. Then, a distributed trust social network analysis (SNA) methodology is proposed to represent trust relationship between experts and compute the trust degree of each expert. Furthermore, the paper combines the maximum average weighted distance and minimum average weighted distance to determine the integrated attribute weights based on distributed trust online reviews, and utilizes relative closeness coefficient to rank the alternatives. An extended TOPSIS method based on distributed trust is developed. Finally, an example is given to illustrate the feasibility of the proposed decision making method.