Method and device for dividing three decision communities based on random walk boundary domain processing

Abstract

The invention discloses a method for dividing three decision communities based on random walk boundary domain processing. The method comprises the following steps: 1) obtaining an abstract network; 2)clustering and granulating that abstract network after initial granulation, dividing the abstract network into a plurality of divided communities, the structure relationship of the divided communities being taken as a first dividing result; 3) obtaining that first partition result of the abstract network corresponding to the maximum value of the module degree of the overlap community; 4) dividingall nodes in that boundary region by using a random walk algorithm; 5), for each node in the updated boundary region, by using a three-branch decision method, processing to obtain a second partitionresult, the second partition result being taken as a target partition result. The invention discloses a device for dividing three decision communities based on random walk boundary domain processing.The application of the invention can improve the precision of the community division, thereby facilitating the analysis and understanding of the network structure, and facilitating the optimization and management of the network.

Description

technical field [0001] The present invention relates to a community division method and device, and more particularly to a three-way decision-making community division method and device based on random walk boundary domain processing. Background technique [0002] Networks exist widely in our real life, such as interpersonal networks in social systems, protein interaction networks in biological systems, the World Wide Web and the Internet in computer networks, etc. Each individual in these networks communicates with others through information exchange channels. individual connections. With the in-depth research on the network, it is found that there are community structures in many actual networks, that is, the entire network is composed of several communities. For example, a network that exists in reality, such as each device in a computer network, can be abstracted into a node, and the network channels between nodes can be abstracted into edges between nodes. It can be fo...

AI Technical Summary

Problems solved by technology

[0004] However, these algorithms only apply the traditional two-branch decision-making method when dealing with overlapping parts, that is, only accept or reject decisions based on existing information.

However, the nodes in the overlapping part often appear in the overlapping part because of insufficient information and cannot determine their ownership. If a decision is forced to be made, it may affect the final result of non-overlapping community division

Therefore, there is a technical problem in the prior art that the accuracy of non-overlapping community division results is not high

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