一种基于数据场的社区发现算法

摘要

在引入数据场的基础上,给出数据场的定义及其形式化的性质描述,进而提出了一种基于数据场的社区发现算法(CDDF).该算法将社区视为一种数据场,选取社区内节点间能量值最高的节点作为中心节点,迭代地进行社区划分.通过仿真实验证明,该算法能够进一步克服传统社区发现方法初始条件选择的困难,有效地消除噪声对社区发现的影响,具有良好的性能.%This paper proposed an algorithm of community detection based on data fields( CDDF). CDDF selected the vertices with the largest energy as center in community, and then processed the partition of community iterated. Experiments prove that using the potential function CODF can deal with the problem of a reasonable initial conditions selection in community detection, avoid the impact of noise, and has good performance.