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中文摘要：
在面向服务的环境中,服务的不透明性、组合结构的复杂性以及用户评价的主观性使得用户难以对组件服务进行有效的信誉评估.针对此问题,提出适用于服务组合的信誉传播算法,将复合服务的信誉评估值公平地传播到各个组件服务.首先,将复合服务建模为Beta混合模型,通过最大期望算法学习复合服务中各个组件的责任及信誉度.其次,基于Shapley值的合作博弈模型计算各个组件服务对复合服务的贡献度,确保所组合的各个服务不会受到额外的奖励或惩罚.最后,理论分析与实验结果表明该算法在保证公平性的前提下,能够正确地将用户提交的信誉评估层次化传播到各个组件服务.
英文摘要：
In service-oriented environment,it is difficult to evaluate component services because of the opaque characteristic of composite services,the complex invocation structures and the subjective reputation rating of service consumers.To address these issues,this paper proposes a reputation propagation algorithm for service composition,in which the subjective ratings can be fairly propagated to each component service.The algorithm first models service composition as the Beta-mixture,and learns the reputation and responsibility of each component by the EM algorithm.Then,based on the characteristics of Shapley values in cooperative gaming theory,the algorithm computes the contribution of each component to its composition,ensuring that no component would obtain extra rewards or punishments.Finally,theoretical analysis and experimental results demonstrate the fairness of the algorithm to hieratically propagate the consumer＇s rating to each component service.
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