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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,...
Searching in complex networks is different from random and regular networks for existing long range connections and hub nodes. So the research on structure and characters of networks will improve the search speed and lower the load of nodes. Though getting the shortest paths is the best choice, in a real network, it is impossible for a node to get global information. For example, there is not a node...
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