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	Detecting Community Structure of Complex Networks by Affinity Propagation
	Liu, Jian ; Wang, Na
	2009
关键词	complex networks community structure affinity propagation shortest path diffusion distance dissimilarity index ALGORITHM
英文摘要	The question of finding the community structure of a complex network has been addressed in many different ways. Here we utilize a clustering method called affinity propagation, associating with some existent measures on graphs, such as the shortest path, the diffusion distance and the dissimilarity index, to solve the network partitioning problem. This method considers all nodes as potential exemplars, and transmits real valued messages between nodes until a high quality set of exemplars and corresponding communities gradually emerges. It is demonstrated by simulation experiments that the algorithms can not only identify the community structure of a network, but also determine the number of communities automatically during the model selection. Moreover, they are successfully applied to several real-world networks, including the karate club network and the dolphins network.; Computer Science, Artificial Intelligence; EI; CPCI-S(ISTP); 0
语种	英语
出处	SCI ; EI
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/406338]
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 Affinity Propagation. 2009-01-01.

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