Local community detection method based on similarity

A detection method and similarity technology, which is applied in the field of complex network analysis, can solve the problems of low efficiency of the global method and cannot be applied to large-scale networks, poor quality of detection results, and unstable performance. stable effect

Inactive Publication Date: 2019-04-12
LANZHOU UNIVERSITY
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Problems solved by technology

[0042] The present invention provides an efficient and stable local community detection method based on similarity - NSA (Node Similarity based Algorithm), which can solve the problem that the glob...

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  • Local community detection method based on similarity
  • Local community detection method based on similarity
  • Local community detection method based on similarity

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Embodiment Construction

[0078] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0079] One, elaborate on the scheme of the present invention:

[0080] The NSA method proposed by the present invention is a community detection method consisting of two stages. In the first stage, the initial community structure is constructed based on the degree centrality and the similarity between vertices. In the second stage, the initial community structure is optimized. Merge some of these small or sparse communities to obtain the final community structure. The overall process framework of the entire community detection method is as follows: figure 1 shown.

[0081] 1. The first stage: building the initial community structure

[0082] The idea of ​​the process is very simple. First select the vertex with the largest degree from the network, and use it as a representative point of a community, and add the most similar neighbor vertex t...

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Abstract

The invention relates to a local community detection method based on similarity, namely an-NSA (Node Similarity based Algorithm). The method is an efficient and stable local community detection methodbased on similarity, and the implementation process of the method comprises two stages, namely, the first stage of constructing an initial community structure of a network, the second stage of optimizing the initial community structure, and merging some small and sparse communities to obtain a final community structure. The method can solve the problem that a global method cannot be suitable fora large-scale network due to low efficiency, and can solve the problems that many existing local methods are unstable in performance and poor in detection result quality. Meanwhile, the invention further provides a measurement index-common metric, the scale and the sparse degree of the communities are comprehensively measured, and the small communities can be effectively merged.

Description

technical field [0001] The invention belongs to the technical field of complex network analysis, and relates to a method for detecting community structures from complex networks, in particular to a local community detection method based on node similarity. Background technique [0002] Community structure is the most prominent structural feature of complex networks. Vertices in the network can be naturally divided into multiple groups. The connections between vertices within the same group are relatively dense, while the edges between vertices in different groups are relatively sparse. Each group is a "community". [0003] In complex networks, communities often correspond to functional units of the network. For example, the grouping of Web pages with the same theme in the WWW network; functional modules in the protein molecular interaction network, metabolic channels in the metabolic network; a group of people with common characteristics in the social network, such as scien...

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Application Information

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IPC IPC(8): G06Q50/00G06K9/62
CPCG06Q50/01G06F18/22
Inventor 程建军苏醒杨海娟李龙杰张景明赵世燕陈晓云
Owner LANZHOU UNIVERSITY
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