用最短路径距离取代网络中用布朗微粒衡量的两节点之间的距离,在此基础上提出了基于最短路径的相异性指数算法。对算法实现过程进行描述,并将算法应用于存在的研究算法分析实例上,说明该算法可行性。把该算法应用于本文构造的虚拟企业网络的社团划分上,划分结果与预期相符。
Using the shortest path distance to replace the distance between two nodes measured by Brownian particles, we present a dissimilarity index algorithm based on the shortest path. The realization process of the algorithm is described. The algorithm is proved feasible by an example of community structure partition by a contrast analysis. The algorithm is applied to community structure partitions of a virtual enterprise network that is built in the paper, the partition result lives up to what is expected.