https://doi.org/10.1140/epjb/e2007-00146-y
Graph kernels, hierarchical clustering, and network community structure: experiments and comparative analysis
1
Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100080, P.R. China
2
Graduate University of Chinese Academy of Sciences, Beijing, 100049, P.R. China
Corresponding author: a zsh@amss.ac.cn
Received:
12
July
2006
Revised:
20
April
2007
Published online:
25
May
2007
There has been a quickly growing interest in properties of complex networks, such as the small world property, power-law degree distribution, network transitivity, and community structure, which seem to be common to many real world networks. In this study, we consider the community property which is also found in many real networks. Based on the diffusion kernels of networks, a hierarchical clustering approach is proposed to uncover the community structure of different extent of complex networks. We test the method on some networks with known community structures and find that it can detect significant community structure in these networks. Comparison with related methods shows the effectiveness of the method.
PACS: 89.75.Hc – Networks and genealogical trees / 89.65.-s – Social and economic systems / 05.10.-a – Computational methods in statistical physics and nonlinear dynamics
© EDP Sciences, Società Italiana di Fisica, Springer-Verlag, 2007