基于Slater社会选择理论的在线服务评价方法

不同用户对于同一在线服务会有不一致的评价标准和偏好,导致其对服务的评分不具备可比性,使用户难以准确选择适合的在线服务。针对该问题,引入Slater社会选择理论提出一种新的在线服务评价方法。对稀疏的评分矩阵进行填充,通过用户对服务评分的相互比较结果,构建以服务为节点、以优先关系为有向边的有向图,并根据其中相似集、前集、后集之间以及内部节点有向边的指向关系,判断所有节点的指向关系及排序,形成服务评价结果。实验结果表明,该方法较Sum法、Average法和Copeland法抗操控性更强,可避免少数用户操控评价结果,并且其符合孔多塞准则,能够体现多数用户的偏好需求。

Online Service Evaluation Method Based on Slater Social Choice Theory

Different users have different evaluation criteria and preferences for the same online service,making their ratings for services incomparable,so users cannot easily select suitable online services.To address the problem,this paper proposes an online service evaluation method based on the Slater Social choice theory.The method fills the sparse rating matrix.It compares user ratings for services to construct a directed graph with services as nodes and preference relations as directed edges.Then it judges points-to relations of all nodes in the graph based on the points-to relations between the similar set,the front set and the later set,as well as points-to relations of directed edges of internal nodes.Thus the order of all nodes can be obtained to generate a service rating result.Experimental results show that compared with Sum,Average and Copeland methods,the proposed method can better avoid a few users manipulating the ratings.The proposed method also conforms to the Slater criteria and can reflect the preference needs of most users.