A method for estimating the number of complex network communities

A complex network and computing method technology, applied in the field of complex network mining

Inactive Publication Date: 2018-12-18
SHANXI UNIV
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  • Abstract
  • Description
  • Claims
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Problems solved by technology

[0005] The technical problem to be solved by the present invention is: how to provide an effective method for estimating the number of communities in complex network communities

Method used

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  • A method for estimating the number of complex network communities
  • A method for estimating the number of complex network communities
  • A method for estimating the number of complex network communities

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Embodiment Construction

[0048] Step 1. For any network node v in the network G(V,E) i , let NG i ={v j |i ,v j > ∈ E} means v i A set of neighboring network nodes, then the network node v i The degree of connectivity can be expressed as d i =|NG i |; Calculate the cohesion of each network node, the higher the cohesion of the network node, the stronger the aggregation ability of the network node for other network nodes in the community, which reflects the density of the internal connection of the community structure. network node v i The calculation method of cohesion includes the following steps:

[0049] Step 1-1. Calculate the network node v i The similarity between its neighbor network nodes, the similarity between two network nodes is the number of common neighbor network nodes of these two network nodes, for example, network node v i and one of its neighbor network nodes v j The similarity sim i,j The calculation method is as formula (1):

[0050] sim i,j =|NG i ∩NG j | (1)

[...

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Abstract

The invention relates to the field of complex network mining, in particular to a method for estimating the number of complex network communities. The method for estimating the number of community in complex network is disclosed. The complex network is denoted as graph and denoted as network G (V, E). The network G (V, E) contain m network nodes, denoted as V= (v1, v2,..., vm), wherein the ith network node (1 <= i <= m) is denoted as vi; There are n connections between nodes in the network, which are represented by n edges, denoted as E= (e1, e2, ..., en), where the first edge (1 <=l<= n) is denoted as el; the number of communities contained in the network G (V, E) and the community center nodes are determined. Without any prior information, it can fully reflect the intrinsic structural characteristics of dense network community and sparse network externality. Estimation accuracy of the number of communities in the network is high, which is conducive to improve the estimation performance of network community discovery algorithm, and has high practical value for the analysis of real network data.

Description

technical field [0001] The invention relates to the field of complex network mining, in particular to a method for estimating the number of complex network communities. Background technique [0002] A complex network generally refers to a network with a large number of nodes and complex connections. The rapid development of Internet technology and the explosive growth of information have brought human society into the Internet age. Our mass production and practice activities are in various complex network environments, such as social networks, protein networks, disease transmission networks, Internet networks, etc. . The uneven distribution of links in these complex networks implies the existence of community structure in the network, and a large number of studies have also shown that the network is usually composed of some communities with obvious structures. The connections between nodes within a community are relatively tight, while the connections between communities a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L12/24
CPCH04L41/14
Inventor 杜航原
Owner SHANXI UNIV
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