Label propagation community structure mining method based on node membership degree

Abstract

A label propagation community structure mining method based on a node membership degree comprises the steps that a unique label is given to each node in a network, and each label is used for representing a community to which the corresponding node belongs; row vectors in a complex network adjacent matrixes are seen as sampling samples of the nodes, and a weight coefficient between two nodes is used as edge weight value; the variance of the node connecting edge weight coefficients is utilized as the node membership degree; in each label updating iteration, only the node labels with the membership degrees larger than the label updating threshold value are updated, and the nodes with the membership degrees smaller than the label updating threshold value are used as overlapping nodes; if the labels are changed, or the label propagation frequency is smaller than the label iteration threshold value, the iteration process is repeatedly executed, and if not, updating is stopped. The label propagation community structure mining method can well detect the overlapping community structure of the complex network under the situation that the time complexity increase is not large, and has the good robustness and accuracy.

Description

technical field [0001] The invention relates to a method in the field of complex networks, in particular to a method for mining a label propagation community structure based on node membership. Background technique [0002] More and more complex systems in real society can be described by complex network models. For example, web pages in the Internet network can be regarded as nodes in complex networks, and hyperlinks between web pages are represented as network edges; social networks can be Different individuals are regarded as nodes, and the links between nodes represent the relationship between individuals; the biological protein network regards different biological proteins as network nodes and uses links to reveal the interaction between different proteins. Therefore, as an effective tool for studying complex systems, various properties of complex networks have attracted extensive attention from scholars from all walks of life. [0003] Community structure is an import...

AI Technical Summary

Problems solved by technology

This method realizes the mining of overlapping community structures by defining the association probability of overlapping nodes, but because the method first uses the GN community splitting algorithm, and then performs the judgment of overlapping nodes and the merging of overlapping communities, the time complexity is relatively high

At the same time, the method needs to pre-specify the threshold parameter, which has a certain impact on the universality of the method

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