Bayesian Complex Network Community Detection Using Nonparametric Topic Model

Author(s):  
Ruimin Zhu ◽  
Wenxin Jiang
2007 ◽  
Vol 07 (03) ◽  
pp. L209-L214 ◽  
Author(s):  
JUSSI M. KUMPULA ◽  
JARI SARAMÄKI ◽  
KIMMO KASKI ◽  
JÁNOS KERTÉSZ

Detecting community structure in real-world networks is a challenging problem. Recently, it has been shown that the resolution of methods based on optimizing a modularity measure or a corresponding energy is limited; communities with sizes below some threshold remain unresolved. One possibility to go around this problem is to vary the threshold by using a tuning parameter, and investigate the community structure at variable resolutions. Here, we analyze the resolution limit and multiresolution behavior for two different methods: a q-state Potts method proposed by Reichard and Bornholdt, and a recent multiresolution method by Arenas, Fernández, and Gómez. These methods are studied analytically, and applied to three test networks using simulated annealing.


2016 ◽  
Vol 46 (4) ◽  
pp. 431-444
Author(s):  
Zhongming HAN ◽  
Xusheng TAN ◽  
Yan CHEN ◽  
Dagao DUAN

2007 ◽  
Vol 56 (1) ◽  
pp. 41-45 ◽  
Author(s):  
J. M. Kumpula ◽  
J. Saramäki ◽  
K. Kaski ◽  
J. Kertész

2019 ◽  
Vol 526 ◽  
pp. 121070 ◽  
Author(s):  
Zheng-Hong Deng ◽  
Hong-Hai Qiao ◽  
Ming-Yu Gao ◽  
Qun Song ◽  
Li Gao

2008 ◽  
Vol 18 (3) ◽  
pp. 033107 ◽  
Author(s):  
Marcos G. Quiles ◽  
Liang Zhao ◽  
Ronaldo L. Alonso ◽  
Roseli A. F. Romero

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