Probabilistic framework for network partition.
Given a large and complex network, we would like to find the partition of this network into a small number of clusters. This question has been addressed in many different ways. In a previous paper, we proposed a deterministic framework for an optimal partition of a network as well as the associated algorithms. In this paper, we extend this framework to a probabilistic setting, in which each node has a certain probability of belonging to a certain cluster. Two classes of numerical algorithms for such a probabilistic network partition are presented and tested. Application to three representative examples is discussed.
LMAM and School of Mathematical Sciences, Peking University, Beijing 100871, People's Republic of China. tieli@pku.edu.cn
Tiejun
T
Li
Jian
J
Liu
Weinan
W
E