[1]LI Wei,YANG Xiaofeng,ZHANG Chongyang,et al.A clustering method for community detection on complex networks[J].CAAI Transactions on Intelligent Systems,2011,6(1):57-62.
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A clustering method for community detection on complex networks

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 6 Number of periods: 2011 1 Page number: 57-62 Column: 学术论文—人工智能基础 Public date: 2011-02-25
Title:
A clustering method for community detection on complex networks
Author(s):
LI Wei;  YANG Xiaofeng;  ZHANG Chongyang;  TANG Kezong;  YANG Jingyu
Department of Computer Science, Nanjing University of Science and Technology, Nanjing 210094, China
Keywords:
complex networks;  community detection;  cluster;  PCA
CLC:
TP311；TP393;N94
DOI:
-
Abstract:
Community detection is important for understanding complex networks. Because of its high complexity, community detection in complex networks has recently attracted significant interest from research groups. In this work, a data analysis perspective was proposed for community detection on complex networks. First, based on the network topology, the nodes of the studied network were projected as data points in a highdimensional space, and the network was associated with a data cloud. Second, principal component analysis (PCA) was used to reduce the highdimensional data cloud into a lowdimensional one, which kept the main structural information. Third, Kmeans algorithms were used to find clusters of the data points in the reduced data cloud, which inferred the communities of the studied network. Experiments on datasets DGG (2mode) and Zachary (1mode) indicated that the proposed method can reveal network communities effectively. The proposed method provided a novel perspective of the community detection of complex networks.
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