Community detection method based on backbone network extension

A backbone network and detection method technology, applied in the field of efficient community detection based on backbone network expansion, can solve the problems of different community division results, high complexity, low algorithm efficiency, etc., achieve wide practical application value, and reduce the calculation scale , the effect of reducing computational complexity

Inactive Publication Date: 2018-07-10
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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  • Claims
  • Application Information

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Problems solved by technology

[0016] 1. For a large-scale network, many algorithms need to introduce various node attribute measurement methods according to different scenarios, such as the number of paths between nodes and node similarity calculations. These measurements require multiple iterations, which will lead to low algorithm efficiency , with greater com

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  • Community detection method based on backbone network extension
  • Community detection method based on backbone network extension
  • Community detection method based on backbone network extension

Examples

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example 1

[0052] Example 1 Karate Club Dataset

[0053] The karate club data set is a data set constructed by American scholar Wayne Zachary from the three-year interaction relationship between members of a university karate club in the United States. The relationship network is as follows: figure 2 shown. The network includes 34 nodes and 78 edges, and each node represents a club member. If there is often a connection between two members, there is a connection between the nodes representing the two members.

[0054] Due to the dispute between the director John A. (node ​​34) and the coach Mr.Hi (node ​​1), the network split into two groups with them as the backbone, such as image 3 , different node colors in the figure represent different communities. Since the network is a real-world network and researchers know the real community structure of the network, this network is often used to test the effectiveness of community detection methods.

[0055] The step that the present inven...

example 2

[0067] Example 2DBLP paper collaborator data set

[0068] The DBLP paper collaborator network has collected most of the computer-related English literature with the author as the core of the research results in the computer field. The present invention only extracts the cooperation situation of 221 authors of conference papers in the field of data mining in the DBLP data set during the 12 years from 2003 to 2014. This dataset has more than 94,000 paper authors and 255,925 cooperative relationships between authors, with an average degree of each node of 8.9. Figure 4 The real topology of some networks when no community division is performed for the DBLP dataset.

[0069] The present invention uses a community detection method based on backbone network extension to calculate the data, and the backbone nodes account for 40% of the total number of nodes in the DBLP data set. After the present invention divides the data in the DBLP data set into communities, the modularity of th...

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Abstract

The invention discloses a community detection method based on backbone network extension, which is used for rapid community discovery in large-scale complex networks. The present invention mainly includes: use the improved PageRank algorithm (WP) based on node weight to calculate the input network, select the node whose WP value is greater than the threshold as the backbone node of the network; traverse the whole network, extract the backbone node and connect any two backbone nodes The edges of the nodes constitute the backbone network; the hierarchical clustering algorithm is run in the backbone network to obtain the backbone community structure; the extension algorithm is used to extend the backbone community to the entire network to obtain the community structure of the overall network. The invention narrows the operating range of the hierarchical clustering algorithm to the backbone network, avoids clustering in the whole network, has relatively small time complexity, and is suitable for community discovery in large-scale complex networks. In addition, the present invention can quickly capture the change details of the overall community by tracking the change of the backbone community, and is suitable for community discovery in a rapidly evolving network.

Description

technical field [0001] The invention relates to the fields of data mining and complex network analysis, in particular to the rapid division of communities under large-scale social networks, and in particular to an efficient community detection method based on backbone network expansion. Background technique [0002] There are a large number of complex systems in the real world, such as biomolecular systems, transportation systems, mail systems, and so on. In order to study the hidden laws in these complex systems and use these laws to serve the needs of human beings in the real world, these complex networks are usually modeled as networks. The entities in the system are regarded as nodes in the network, and the links between entities are regarded as connections or edges in the network. For example, the nodes in the transportation network correspond to intersections, and the edges represent the roads between intersections; the nodes in the protein interaction network represe...

Claims

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Application Information

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IPC IPC(8): H04L12/26
Inventor 刘瑶刘峤秦志光其他发明人请求不公开姓名
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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