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Network graph segmentation method and storage medium

A network graph and network node technology, applied in the field of community mining of complex network graphs, can solve problems such as low efficiency, slow computing speed, difficult parallel computing, etc., and achieve the effect of improving analysis efficiency, increasing computing speed, and improving user experience

Pending Publication Date: 2020-06-12
NAT UNIV OF DEFENSE TECH
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

The calculation amount of the Louvain algorithm is mainly concentrated in the first stage, and its calculation process is a typical serial algorithm process, in which the calculation of each node depends on the calculation result of the previous node, and the calculation is closely dependent, so it is difficult to directly Parallel computing, slow operation speed, low efficiency

Method used

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  • Network graph segmentation method and storage medium
  • Network graph segmentation method and storage medium
  • Network graph segmentation method and storage medium

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Embodiment 1

[0033] The embodiments of the present disclosure are divided based on a network graph with 16 nodes, image 3 It is a schematic diagram showing a network diagram according to an exemplary embodiment.

[0034] Such as image 3 As shown, the network graph has 16 network nodes, namely the set N 1 The middle elements are {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15};

[0035] This implementation selects set N 1 The middle node 0 is used as the starting point, and the neighbor nodes of search node 0 are {2, 3, 4, 5};

[0036] Take the neighbor node 2 of node 0 and search the neighbor node {0, 1, 4, 5, 6} of node 2;

[0037] Then take the neighbor node 3 of node 0 and search the neighbor node {0, 7} of node 3;

[0038] Then take the neighbor node 4 of node 0 and search for the neighbor node {0, 1, 2, 10} of node 4;

[0039] Then take the neighbor node 5 of node 0, and search the neighbor node {0, 2, 7, 11} of node 5;

[0040] All the searched nodes {0, 1, 2, 3, 4, 5, 6, 7, 10, 11} from...

Embodiment 2

[0133] The network graph segmentation method provided by the embodiments of the present disclosure is suitable for weightless network graphs containing more than two network nodes. Taking a complex social network graph containing millions of nodes as an example, a network graph segmentation method is explained.

[0134] figure 2 Is a schematic flowchart of a method for dividing a network diagram according to an exemplary embodiment;

[0135] Such as figure 2 As shown, a network graph segmentation method includes:

[0136] S201: Form all nodes in the current graph into a set N;

[0137] S202: Take any node in the set N and mark it as Node0;

[0138] S203: Traverse the neighbor node Node0i of Node0;

[0139] S204: Traverse the neighbor node Node0im of Node0i;

[0140] S205. Add the node Node0 to the isolated set Sj, and delete the traversed nodes Node0, Node0i, and Node0im from the set N;

[0141] S206: Determine whether the set N is an empty set. When the set N is an empty set, perform st...

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Abstract

The invention discloses a network graph segmentation method, which comprises the following steps of: randomly taking one node in an obtained network graph node set as a first node, traversing all neighbor nodes of the first node to serve as a first neighbor node set, traversing all neighbor nodes of the first neighbor node set to serve as a second neighbor node set; deleting a first node, a firstneighbor node set and a second neighbor node set in the node set, and adding the first node into an isolated set; repeating the above steps until the node set becomes an empty set, obtaining an isolated set after segmentation, continuing to obtain all network node sets in the graph, and deleting network nodes contained in the isolated set to obtain a remaining node set; and repeating the steps until the residual node set is zero. By means of the method, when the community mining algorithm is used for social network analysis, the operation speed can be increased, the analysis efficiency can beimproved, and the mining and analysis capacity for large-scale social networks can be improved.

Description

Technical field [0001] The present invention relates to the field of community discovery of complex network graphs, in particular to a network graph segmentation method and storage medium. Background technique [0002] With the rapid development of science and technology, the complex network information formed by social platforms, Internet websites, online products and customers can no longer be represented by traditional list, matrix and other structured data. Therefore, graph this kind of unstructured data The structure is used to quantitatively describe this complex network. It describes the objects in the network and the connection relationship between the objects. The algorithm based on the data structure of the graph is called the graph algorithm. The community discovery algorithm is a kind of graph algorithm. In a complex network graph, some nodes are more closely connected, and some nodes are more sparsely connected. These closely connected nodes are relative to sparsely ...

Claims

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Application Information

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IPC IPC(8): G06F16/901G06F16/906
CPCG06F16/9024G06F16/906
Inventor 苏华友郄航窦勇姜晶菲李荣春牛新乔鹏潘衡岳
Owner NAT UNIV OF DEFENSE TECH
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