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Overlapping communities in complex network is a common phenomenon in real  world network. The overlapping community structure can more accurately  obtain the actual structure information in the network. But at present the  study of overlapping community division algorithm is relatively less, facing  the problems of the low accurate rate. Based on this, this paper presents  algorithms OCNS for detecting community overlapping base on node similarity.  The algorithm calculates similarity between two nodes in the network by  means of Jaccard similarity measure formula. Then the related nodes are  adaptive merged according to the similarity value, combining with the  community according to the change of modularity. The process of partitioning  can not only accurately merge closely linked nodes in the network, but also  find the overlapping nodes and bridge nodes between communities. The  experiment proved the algorithm is effective to detect the overlapping  community and has obvious advantages in the division of baseline social  network Zachary and dolphin network, and the quality of division better than  other existing partitioning algorithm.

Detecting overlapping community in complex network based on node similarity