  Many real-world networks such as the gene networks, protein-protein
interaction networks and metabolic networks exhibit community structures,
meaning the existence of groups of densely connected vertices in the networks.
Many local similarity measures in the networks are closely related to the
concept of the community structures, and may have positive effect on community
detection in the networks. Here, various local similarity measures are used to
extract the local structural information and then are applied to community
detection in the networks by using the edge-reweighting strategy. The effect of
the local similarity measures on community detection is carefully investigated
and compared in various networks. The experimental results show that the local
similarity measures are crucial to the improvement for the community detection
methods, while the positive effect of the local similarity measures is closely
related to the networks under study and the applied community detection
methods.
