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Community discovery method based on maximum clique and strongly connected component

A connected component and community discovery technology, applied in the field of specific community structure discovery, can solve problems such as low efficiency and difficulty in large-scale graph model data processing

Inactive Publication Date: 2021-07-06
BEIJING INSTITUTE OF TECHNOLOGYGY
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] The purpose of the present invention is to provide a community discovery method to solve the problems of large-scale graph model data processing difficulty and low efficiency

Method used

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  • Community discovery method based on maximum clique and strongly connected component
  • Community discovery method based on maximum clique and strongly connected component
  • Community discovery method based on maximum clique and strongly connected component

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Embodiment Construction

[0028] Concept introduction:

[0029] 1. Given a directed graph G=(V,E), if the subset of vertices S is called a maximal directed clique if the following conditions are met:

[0030] (1) In the base graph of G, the derived subgraph of all vertices in S is a clique;

[0031] (2) In G, the derived subgraph of S is strongly connected;

[0032] (3) There is no larger vertex set that contains S and satisfies (1) and (2).

[0033] 2. In an undirected graph, a subgraph satisfying that the degree of all vertices in the subgraph is greater than or equal to k is called the k-core of the graph.

[0034] 3. For a directed graph, if starting from any vertex and returning to the vertex through several edges, the graph is called a directed acyclic graph.

[0035] 4. For all vertices of the graph, there is an arrangement (v_1,v_2,...,v_n) such that each vertex v_i has a degree in the derived subgraph G[{v_i,...,v_n}] formed by it and the vertices after it The smallest, this arrangement ...

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Abstract

The invention discloses a community discovery method based on a maximum clique and a strongly connected component. The community discovery method is suitable for a community structure with a base map being a clique and connecting edges between vertexes meeting strongly connected in a directed network. Through three steps of preprocessing, step-by-step enumeration and result duplication judgment, a maximum directed group community of which the number of all vertexes is not less than a given threshold is finally obtained. According to the community discovery method, in large-scale graph data processing, the enumeration redundant calculation amount is reduced, parallel calculation is achieved, and efficiency is high.

Description

technical field [0001] The application belongs to the technical field of data mining, and in particular relates to a method for discovering a specific community structure in a directed network. Background technique [0002] With the rapid development of digital technology, graph models have been widely used to represent a large amount of information and complex relationships between data, and many complex systems in the real world can be abstracted in the form of complex networks. Different from randomly generated graph data, real networks often contain many sub-network structures, and the individual relationships in the same sub-network are closely related, while the individual relationships between different sub-networks are relatively sparse. Through the connection of the network, nodes of different natures and types form a community structure with rich relationships. [0003] In the real world, nodes often belong to multiple communities. For example, most proteins in a ...

Claims

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Application Information

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IPC IPC(8): G06F16/901G06F16/903G06F16/2453G06F16/2458
CPCG06F2216/03G06F16/24532G06F16/2465G06F16/9024G06F16/90335
Inventor 陈久健李荣华王国仁金福生秦宏超
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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