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TSM-Trust: A Time-Cognition Based Computational Model for Trust Dynamics

机译:TSM-Trust:基于时间认知的信任动态计算模型

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This paper proposes a hierarchical network model for trust evaluation after introducing time cognition, which mainly considers trust dynamics. In this model, the Temporal Sequential Marker (TSM) is tagged on each item in an implicit or explicit manner and all items are divided into several layers according to their TSMs information. Furthermore, three different kinds of forgetting effects are investigated and quantified for the computing of TSM- Trust. These effects are: distance effect, boundary effect and hierarchical effect. Next, according to the Ebbinghaus curve of forgetting, cosine function is used to model the forgetting process of Experience Information (EI) approximately, the D-S theory is exploited to build up a computational dynamic trust (TSM-Trust) model based on our proposed hierarchical network model. Finally, our future work is pointed out after analysizing the limitations of this paper.
机译:在引入时间认知之后,本文提出了一种用于信任评估的分层网络模型,该模型主要考虑信任动态。在此模型中,以隐式或显式方式在每个项目上标记时间顺序标记(TSM),并且根据其TSM信息将所有项目分为几层。此外,为计算TSM-Trust,研究并量化了三种不同的遗忘效应。这些效应是:距离效应,边界效应和分层效应。接下来,根据遗忘的艾宾霍斯曲线,使用余弦函数对体验信息(EI)的遗忘过程进行近似建模,利用DS理论基于我们提出的层次结构建立了计算动态信任(TSM-Trust)模型。网络模型。最后,在分析了本文的局限性之后指出了我们今后的工作。

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