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Backbone network extraction method and device, computer equipment and storage medium

A backbone network and extraction method technology, applied in the field of information processing, can solve problems such as deletion of local information and loss of important information in the backbone network

Pending Publication Date: 2021-12-10
INST OF INFORMATION ON TRADITIONAL CHINESE MEDICINE CACMS
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The inventor found in the actual data test that although the purpose of the difference screening algorithm is to protect local important information from being lost, due to the use of a globally unified significance level, local information may still fail to pass the significance test of the significance level was deleted, resulting in the loss of important information of the extracted backbone network

Method used

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  • Backbone network extraction method and device, computer equipment and storage medium
  • Backbone network extraction method and device, computer equipment and storage medium
  • Backbone network extraction method and device, computer equipment and storage medium

Examples

Experimental program
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Effect test

Embodiment 1

[0050] This embodiment provides a backbone network extraction method, figure 1 It is a flow chart illustrating that according to some embodiments of the present invention, network brackets are sequentially extracted from the first to-be-extracted network, multiple sub-backbone networks are obtained, and multiple sub-backbone networks are summed to form a backbone network. Although the processes described below include operations in a particular order, it should be clearly understood that these processes may also include more or fewer operations, which may be performed sequentially or in parallel (e.g., using parallel processors) or multi-threaded environment).

[0051] This embodiment provides a backbone network extraction method, which can be used to reduce complex network structures in fields such as medicine, biology, society, and communication to form a backbone network containing a large amount of important information. Especially for the complex network structure establ...

Embodiment 2

[0143] This embodiment provides a backbone network extraction device, which can be used to reduce complex network structures in fields such as medicine, biology, society, and communication to form a backbone network containing a large amount of important information. Such as Figure 7 shown, including:

[0144] The acquiring module 401 is configured to acquire the first network to be extracted. For details, please refer to the relevant description of step S101 in Embodiment 1, which will not be repeated here.

[0145] The extraction module 402 is configured to extract a network bracket from the first network to be extracted to obtain a first sub-backbone network, until the network bracket cannot be extracted from the N+1th network to be extracted under a certain significance level; Wherein, the N+1th network to be extracted is the network to be extracted obtained by removing the Nth sub-backbone network from the Nth network to be extracted, and the Nth sub-backbone network i...

Embodiment 3

[0149] This embodiment provides a computer device, such as Figure 5 As shown, the device includes a processor 501 and a memory 502, wherein the processor 501 and the memory 502 can be connected through a bus or other methods, Figure 5 Take connection via bus as an example.

[0150] The processor 501 may be a central processing unit (Central Processing Unit, CPU). The processor 501 may also be other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), graphics processors (Graphics Processing Unit, GPU), embedded neural network processors (Neural-network Processing Unit, NPU) or other Dedicated deep learning coprocessor, application specific integrated circuit (Application Specific Integrated Circuit, ASIC), field programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components and other chips, or a combination of the above-mentioned typ...

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Abstract

The invention relates to the field of information processing, in particular to a backbone network extraction method and device, computer equipment and a storage medium; the method comprises the following steps: obtaining a first to-be-extracted network; extracting a network support from the first to-be-extracted network to obtain a first sub-backbone network until the network support cannot be continuously extracted from the (N + 1) th to-be-extracted network at a specific significance level, wherein the (N + 1) th to-be-extracted network is a to-be-extracted network obtained by removing an Nth sub-backbone network from an Nth to-be-extracted network, and the Nth sub-backbone network is obtained by extracting a network support from the Nth to-be-extracted network; and summing the N sub-backbone networks to form the backbone network. Compared with a network extracted by an existing difference screening algorithm, the obtained backbone network can fully contain important information in an original network, so that all local important information can be finally reserved.

Description

technical field [0001] The invention relates to the field of information processing, in particular to a backbone network extraction method, device, computer equipment and storage medium. Background technique [0002] There are complex network structures in the fields of medicine, biology, society, and communication, but these network structures have the characteristics of a large number of nodes, a small network diameter, a distribution of node degrees, and a distribution of weights of network supports that exhibits an equipotential distribution. That is, a large amount of information is concentrated in a small number of nodes or network supports in the network, and the distribution of information is very uneven. Therefore, both the visualization of the network and the extraction of key information will become very difficult. [0003] The key to solving the above problems is to reduce the network structure, reduce the information of lower value in the network, and retain th...

Claims

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Application Information

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IPC IPC(8): G06F16/901G06F16/9035G06F17/18
CPCG06F16/9024G06F16/9035G06F17/18
Inventor 文天才周雪忠杨杰张磊
Owner INST OF INFORMATION ON TRADITIONAL CHINESE MEDICINE CACMS
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