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	Detecting community structure of complex networks by simulated annealing with optimal prediction
	Liu, Jian ; Wang, Na
	2009
英文摘要	Given a large and complex network, we would like to find the best partition of this network into a small number of clusters. This question has been addressed in many different ways. Here we utilize the simulated annealing strategy to maximize the modularity of a network with our previous hard partitioning formulation for the community structure, which is based on the optimal prediction of a random walker Markovian dynamics on the network. It is demonstrated that this simulated annealing with optimal prediction (SAOP) algorithm can efficiently and automatically determine the number of communities during the cooling procedure associated with iterative steps. Moreover, the algorithm is successfully applied to three model problems. ?2009 IEEE.; EI; 0
语种	英语
出处	EI
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/315489]
专题	数学科学学院
推荐引用方式 GB/T 7714	Liu, Jian,Wang, Na. Detecting community structure of complex networks by simulated annealing with optimal prediction. 2009-01-01.

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