Abstract
As an important global geometric quantity, edge betweennesses can reect the impact of corresponding edges in the entire network, which have a very strong practical signicance. However, edge betweenness ignores the relationship between the vertices which connected indirectly with the edge. This paper rst puts forward a dissimilarity matrix based on a novel edge betweenness, and applies it to a spectral clustering algorithm and nally, in order to detect the community structure in complex networks with this improved algorithm, we use a correction step which is based on the gravitation force of the community. This algorithm has been tested on computer-generated networks and typical real world networks. Compared to GN, PBD, GK and DA, the proposed algorithm possesses an apparent advantage.
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