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Community detection method fusing Embedding enhanced topology and node content information

A technology of node content and detection method, which is applied in the field of complex network analysis, can solve problems such as long calculation time, and achieve the effect of improving accuracy and enhancing topology information

Pending Publication Date: 2021-10-19
NANTONG UNIVERSITY
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  • Application Information

AI Technical Summary

Problems solved by technology

With the development of Internet technology, the information contained in complex networks tends to increase exponentially, resulting in a long calculation time for large-scale network community detection.

Method used

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  • Community detection method fusing Embedding enhanced topology and node content information
  • Community detection method fusing Embedding enhanced topology and node content information
  • Community detection method fusing Embedding enhanced topology and node content information

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Embodiment 1

[0039] see Figure 1 to Figure 2 , the technical solution provided by the present invention is a community detection method that integrates Embedding enhanced topology and node content information,

[0040] (1) Use the data set to obtain community information. The data set used in this example is the LFR artificial network. Regarding the LFR artificial network, the necessary instructions are as follows:

[0041] a) The degrees of all nodes are generated using a power-law distribution with exponent γ. The maximum node degree is set to k max , the minimum value is k min , the average degree is set to .

[0042] b) Each node has a 1-μ proportion of edges connecting to nodes within its community, and correspondingly, a μ proportion of edges connecting to nodes outside its community. μ is called the mixing coefficient, which is used to describe the fuzzy degree of the community structure in the network.

[0043] c) The size of all communities is generated using a power-l...

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Abstract

The invention provides a community detection method fusing Embedding enhanced topology and node content information. The method comprises the following steps: acquiring edges between complex network summarizing nodes and a text data set on the nodes; respectively carrying out matrix processing and one-hot processing on the network topology and the node content information, and carrying out Embedding processing on the network topology based on a Node2vec method so as to obtain Embedding information of the complex network; associating the information to construct a community detection model fusing and strengthening network topology and node content; and deducing model parameters through model optimization, and evaluating clustering based on the model parameters. The method has the beneficial effects that the negative effects of insufficient network topology representation and sparsity are relieved, and the method has a good theoretical application value for community detection fusing network topology and content information.

Description

technical field [0001] The invention relates to the technical field of complex network analysis, in particular to a community detection method that integrates Embedding enhanced topology and node content information. Background technique [0002] There are a large number of complex networks in the real world, such as social networks, the Internet, telephone networks, and gene function networks. Mining the community structure in the network helps to understand the main function or structure of the complex network and predict the behavior of nodes, which is one of the important tasks of complex network analysis. Traditional community detection is often based on the main idea that the links between nodes belonging to the same community are tight, and the links between nodes belonging to different communities are sparse. However, complex networks also contain rich content information, which can assist link information (also known as network topology) to improve the accuracy of ...

Claims

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Application Information

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IPC IPC(8): G06F16/9532
CPCG06F16/9532
Inventor 曹金鑫许伟忠丁卫平张晓峰鞠恒荣黄嘉爽程纯
Owner NANTONG UNIVERSITY