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Method for identifying subnet type in directed complex network based on graph theory

A technique for identifying subnets in complex networks, which is applied in the field of identifying subnet types in directed complex networks based on graph theory, and can solve problems such as inability to adapt to complex work, lack of division tools, and less involvement of subnetworks

Inactive Publication Date: 2021-09-14
北京大唐神州科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0014] 2. Focus on mining the community structure of undirected networks. Most of the current community discovery algorithms are unable to adapt to complex tasks, especially for emerging social networks, knowledge graphs and other sub-networks with directional weights, which are less involved and lack efficient division tools.

Method used

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  • Method for identifying subnet type in directed complex network based on graph theory
  • Method for identifying subnet type in directed complex network based on graph theory
  • Method for identifying subnet type in directed complex network based on graph theory

Examples

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Embodiment 1

[0189] Refer to attached Figure 1-8 , according to a specific embodiment of the present invention, the method for identifying subnet types in a directed complex network based on graph theory provided by the present invention is described in detail.

[0190] The invention provides a method for identifying subnet types in directed complex networks based on graph theory, comprising the following steps:

[0191] Calculate the graph feature quantity of all nodes in the directed complex network, the graph feature quantity includes the degree, the distance between two points, the clustering coefficient, the average distance of all nodes in the directed complex network and the average value of all nodes in the directed complex network Agglomeration coefficient;

[0192] Preliminary identification of sub-networks in the directed complex network according to the graph feature quantities and preliminary identification conditions of all nodes in the directed complex network;

[0193] T...

Embodiment 2

[0223] Refer to attached Figure 1-8 , according to a specific embodiment of the present invention, the method for identifying subnet types in a directed complex network based on graph theory provided by the present invention is described in detail.

[0224] Calculate the graph feature quantity of all nodes in the directed complex network, the graph feature quantity includes the degree, the distance between two points, the clustering coefficient, the average distance of all nodes in the directed complex network and the average value of all nodes in the directed complex network Agglomeration coefficient;

[0225] Preliminary identification of sub-networks in the directed complex network according to the graph feature quantities and preliminary identification conditions of all nodes in the directed complex network;

[0226] Preliminary identification also includes preliminary identification of star network subnets, including the following steps:

[0227] Traverse all the nodes...

Embodiment 3

[0243] Refer to attached Figure 1-8 , according to a specific embodiment of the present invention, the method for identifying subnet types in a directed complex network based on graph theory provided by the present invention is described in detail.

[0244] Calculate the graph feature quantity of all nodes in the directed complex network, the graph feature quantity includes the degree, the distance between two points, the clustering coefficient, the average distance of all nodes in the directed complex network and the average value of all nodes in the directed complex network Agglomeration coefficient;

[0245] Preliminary identification of sub-networks in the directed complex network according to the graph feature quantities and preliminary identification conditions of all nodes in the directed complex network;

[0246] Preliminary identification includes initial identification of chain network subnets, including the following steps:

[0247] Gradually traverse each node o...

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Abstract

The invention provides a method for identifying different types of subnets in a complex network based on a graph theory, and belongs to the field of computer technology application. The method comprises the following steps: firstly, acquiring a topological graph of the directed complex network, calculating graph characteristic quantities of all nodes in the network, preliminarily identifying different types of sub-networks by traversing all the nodes in the directed complex network according to the graph characteristic quantities of all the nodes and preliminary identification conditions, and then verifying the preliminarily identified sub-networks, and for the sub-network with the preliminary identification error, removing the preliminary identification result. According to the method provided by the invention, the required data is simple, and the subnet type identification accuracy is higher.

Description

technical field [0001] The invention relates to the field of computer application technology, in particular to a method for identifying subnet types in directed complex networks based on graph theory. Background technique [0002] Due to the large number of nodes and edges in large-scale complex networks, there are complex topological structures and hierarchical relationships, which are difficult to study systematically with general graph analysis methods. For this reason, the network structure is generally analyzed through community discovery. Community discovery is to use the information contained in the graph topology to parse out its modular node set from the complex network, which helps to study the modules, functions and evolution of the entire network in a divide-and-conquer manner, and to understand complex networks more accurately. Principles of organization, topology and dynamics of systems. [0003] The main methods of current research on community structure inc...

Claims

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Application Information

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IPC IPC(8): G06Q50/00G06F16/901
CPCG06Q50/01G06F16/9024
Inventor 不公告发明人
Owner 北京大唐神州科技有限公司
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