基于先验估计的传播中心溯源算法

Propagation Source Tracing Algorithm Based on Priori Estimation

针对多数信息传播溯源算法未考虑先验估计对溯源的作用和价值,造成溯源检测率较低、错误距离较大等问题,文中利用易感-感染模型(SI)模拟信息在加权网络上的传播过程,提出基于先验估计的传播中心溯源算法.算法综合考虑邻居节点中感染节点和未被感染节点,根据它们的数量关系作为源节点先验估计值,有效弥补现有溯源算法先验估计不足的缺陷.在人工网络和真实网络上的实验表明,文中算法检测率较高、错误距离较小、真实源节点排名精确度较高.

The deficiencies of most existing spreading source detection methods are low detection rate and large error distance due to the disregard of priori estimation of source node.The infection model,susceptible-infected(SI),is utilized to simulate the propagation process of information in weighed social networks,and a spreading source tracing algorithm based on priori estimation is proposed.Both infected and uninfected nodes of neighborhood are considered,and priori estimations are assigned to the source node according to the number relationship between infected nodes and uninfected nodes.Experiments on artificial and real networks indicate that the proposed algorithm achieves a high detection rate,a small error distance and a high accuracy of real source node ranking.