Dynamic trust model based on recommendation chain classification in complex network environment - Lin ZHANG; Huan XING; Ru-chuan WANG; Chao-jie WU (Tongxin xuebao)
According to the recommendation information processing problem in complex network environment,a trust model based on the recommendation chain classification was proposed.The classification method was based on honesty attribute of nodes,which could choose an effective recommendation chain on the basis of practical experience data.The recommendation information dissemination parameters were based on the information gain,which made recommendation information be more accurate.The factor of time was also considered in this model.The ability of interaction and the one of honesty were distinguished clearly.The concept of information entropy in information theory was used in the final ag-gregation calculation of direct trust and recommendation trust,which could get rid of the ambiguity of the previous sub-jective parameter settings.The main polymerization parameters could be continuously corrected with the interactions in order to achieve the situation being closest to the reality.Simulation results show the validity of recommendation chain classification and the rationality of the parameter settings in the proposed model.