Fuzzy overlapping community detection based on local random walk and multidimensional scaling
Fuzzy overlapping community detection based on local random walk and multidimensional scaling
复制标题
基于局部随机游走和多维尺度的模糊重叠社区检测
DOI：
10.1016/j.physa.2013.08.028
复制
发表时间：
2013-12
期刊：
影响因子：
--
通讯作者：
Pan, Lin
中科院分区：
文献类型：
--
作者：
Wang, Wenjun;Liu, Dong;Liu, Xiao;Pan, Lin
模糊重叠社区是一种重要的重叠社区，每个节点在不同程度上属于每个社区。它存在于许多真实网络中，但如何识别模糊重叠社区仍然是一个具有挑战性的任务。本文引入了局部随机游走的概念和一种新的距离度量。基于新的距离度量，首先计算网络各节点之间的不相似度指数。然后，为了尽可能保持原始节点距离，通过多维尺度（MDS）将网络结构映射到低维空间。最后，利用模糊c均值聚类方法寻找网络中的模糊群落。实验结果表明，该算法在人工网络和真实网络中都能有效识别模糊重叠群体。
A fuzzy overlapping community is an important kind of overlapping community in which each node belongs to each community to different extents. It exists in many real networks but how to identify a fuzzy overlapping community is still a challenging task. In this work, the concept of local random walk and a new distance metric are introduced. Based on the new distance measurement, the dissimilarity index between each node of a network is calculated firstly. Then in order to keep the original node distance as much as possible, the network structure is mapped into low-dimensional space by the multidimensional scaling (MDS). Finally, the fuzzy c-means clustering is employed to find fuzzy communities in a network. The experimental results show that the proposed algorithm is effective and efficient to identify the fuzzy overlapping communities in both artificial networks and real-world networks.
登录
查看更多内容
DOI：
10.1016/j.socnet.2008.03.001
发表时间：
2008-07
期刊：
Soc. Networks
影响因子：
--
作者：
George B. Davis;Kathleen M. Carley
通讯作者：
George B. Davis;Kathleen M. Carley
影响因子：
3.7
作者：
Piccardi C
通讯作者：
Piccardi C
影响因子：
4.2
作者：
D. Hand;H. Mannila;Padhraic Smyth
通讯作者：
D. Hand;H. Mannila;Padhraic Smyth
影响因子：
11.9
作者：
Kolen, JF;Hutcheson, T
通讯作者：
Hutcheson, T
影响因子：
2.4
作者：
Psorakis, Ioannis;Roberts, Stephen;Sheldon, Ben
通讯作者：
Sheldon, Ben