A novel community detection algorithm based on simplification of complex networks
A novel community detection algorithm based on simplification of complex networks
复制标题
一种基于复杂网络简化的社区发现算法
DOI：
10.1016/j.knosys.2017.12.007
复制
发表时间：
2018-03-01
影响因子：
8.8
通讯作者：
Guo, Yike
中科院分区：
文献类型：
--
作者：
Bai, Liang;Liang, Jiye;Guo, Yike
Efficiently discovering the hidden community structure in a network is an important research concept for graph clustering. Although many detection algorithms have been proposed, few of them provide a visual understanding of the community structure in a network. In this paper, we define two measurements about the leading and following degrees of a node. Based on the measurements, we provide a new representation method for a network, which transforms it into a simplified network, i.e., weighted tree (or forest). Compared to the original network, the simplified network can easily observe the community structure. Furthermore, we present a detection algorithm which finds out the communities by min-cutting the simplified network. Finally, we test the performance of the proposed algorithm on several network data sets. The experimental results illustrate that the proposed algorithm can visually and effectively uncover the community structure. (C) 2017 Elsevier B.V. All rights reserved.
