Community discovery method based on Louvain algorithm, computer equipment and readable storage medium thereof

Abstract

The invention relates to a community discovery method based on a Louvain algorithm, computer equipment and a readable storage medium thereof. The method comprises the following steps: S1, generating agraph representing a network structure according to input data, wherein the graph comprises nodes and edges; S2, taking each node of the graph as an independent community; S3, performing inner-layercirculation and updating the affiliated community of each node; S4, repeating the step S3 until the percentage of the modularity change of the graph is less than a first threshold value and the current cycle index is an even number, or the inner-layer cycle index is greater than a second threshold value and the current cycle index is an even number, and ending the inner-layer cycle; S5, performing connectivity check on each community; if the communities are not connected, segmenting the communities into a plurality of connected sub-graphs, and taking each connected sub-graph as an independentcommunity; S6, compressing all the communities, and compressing each community into a node; and S7, inputting the result of the step S6 into the step S2, repeating the steps S3 to S6, and outputtingthe result until the modularity of the graph does not change any more or the percentage of the change is smaller than a third threshold.

Description

Technical field [0001] The present invention relates to the technical field of data mining, in particular to a method for community discovery based on Louvain algorithm, computer equipment and a readable storage medium thereof. Background technique [0002] Complex networks are the abstraction of complex systems. In reality, many complex systems can be described and analyzed by the relevant characteristics of complex networks, such as the World Wide Web and social relations networks. Among them, the nodes in the network represent the individuals in the system, and the edges represent the relationships between individuals. Complex networks have always been a research hotspot in many fields. Among them, the community structure is a common feature in complex networks. Research on communities in the network plays a vital role in understanding the structure and function of the entire network, and can help us analyze and predict The interaction between the elements of the entire netwo...

AI Technical Summary

Problems solved by technology

[0007] The advantage of the label propagation algorithm is that it is simple and intuitive to implement, but its accuracy is general and its performance is unstable; the Infomap algorithm has high accuracy but a large amount of calculation; the Louvain algorithm has good accuracy and a small amount of calculation, and is more suitable for large-scale complex networks.

However, the public Louvain algorithm is a serialization algorithm and cannot be applied in distributed computing systems

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