Community discovery method used for complex network

Abstract

The invention puts forward a community discovery method used for a complex network. An algorithm designs a node transition probability through the analysis of a network topology structure, the significance of the node for the network community is evaluated on the basis of a random walk method, then, the node with the high significance is taken as a core to construct the network community, and finally, a community structure is regulated through a community edge trimming method. Compared with an existing method based on random walk, CDATP (Community Detection Algorithm Based on Asymmetric Transfer Probability of Nodes) exhibits the node design transition probability in the network, and the degree of importance of the node for the community is evaluated through the local transition of the node.

Description

technical field [0001] The invention relates to the fields of computer science and social network, and proposes a network community detection algorithm based on asymmetric transfer probability of nodes (CDATP). Aiming at the drawbacks of existing community discovery algorithms, a new node transition probability measurement method and a community division method based on event propagation rules are proposed. Background technique [0002] In recent years, the community structure ubiquitous in the network has received extensive attention from scholars at home and abroad. The research on community discovery has also been applied to many fields and achieved good results. [0003] Using random walk for community discovery is one of the more mainstream research methods. Random walk is a method based on the Markov model. Its main idea is to release a large number of random walkers with an initial distribution. After the diffusion process, the distribution function of the walkers c...

AI Technical Summary

Problems solved by technology

[0006] The present invention mainly solves the technical problems existing in the prior art, etc.; provides a network community detection algorithm based on asymmetric transfer probability of nodes (CDATP) for the existing community discovery In view of the shortcomings of the algorithm, a new node transition probability measurement method and a community division method based on event propagation rules are proposed. On the one hand, it can make full use of the network topology information and reflect the asymmetry of nodes; The need for experimentation and expert knowledge

Specifically, this method aims at the problem that existing community discovery algorithms do not perform well in real networks, and combines the event propagation law with the random walk method to evaluate the importance of nodes to the community, and divide the community on this basis

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