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

摘要

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 analyzing the limitations of this paper.