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A method and a device for identifying super nodes in a relational graph constructed by mass data

A massive data and super node technology, applied in the field of data processing, can solve problems such as paralyzed calculation of relational graphs, low recognition efficiency, and dependence on expert experience

Inactive Publication Date: 2019-06-04
AGRICULTURAL BANK OF CHINA
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  • Abstract
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Problems solved by technology

However, if the complex network contains super nodes, these nodes will receive too many messages after the first round of propagation, which will paralyze the relationship graph and make it impossible to proceed to the next step
[0005] In the existing technology, it is usually judged by artificial experience which nodes have the degree of super nodes, but relying too much on expert experience, the identification efficiency is low, and some meaningful points may also be identified as super nodes

Method used

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  • A method and a device for identifying super nodes in a relational graph constructed by mass data
  • A method and a device for identifying super nodes in a relational graph constructed by mass data
  • A method and a device for identifying super nodes in a relational graph constructed by mass data

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Embodiment Construction

[0040] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0041] refer to figure 1 , which shows a schematic flowchart of a method for identifying super nodes in a relationship graph constructed from massive data disclosed in an embodiment of the present invention. In this embodiment, the method includes:

[0042] S101: Construct a relationship graph of massive data; the relationship graph includes nodes and edges formed by connecting two nodes;

[0043] In this embodiment, when processing different data, a relation...

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Abstract

The invention discloses a method and device for identifying super nodes in a relational graph constructed by mass data. The method comprises the steps of constructing the relational graph of the massdata, calculating the degree of each node, calculating the occurrence probability of the degree of each node according to power law distribution, and removing the nodes with the occurrence probabilitysmaller than a preset threshold value. Therefore, the super nodes in the complex network can be automatically identified, and the super nodes are identified according to the power law distribution, so that the probability of removing meaningful nodes is reduced.

Description

technical field [0001] The present invention relates to the field of data processing, in particular to a method and device for identifying super nodes in a relationship graph constructed from massive data. Background technique [0002] With the development of Internet technology, a large amount of user data is recorded on the computer platform. In order to conduct research on certain issues, such as the analysis of fraudulent blacklist label propagation or the analysis of anti-money laundering transfer relationships, it is necessary to use massive data to generate complex relationship networks. , and analyze complex networks. [0003] However, scale-free networks are included in complex networks. Scale-free networks have serious heterogeneity. A few nodes often have a large number of connections, while most nodes do have a small number of connections. However, when researching scale-free networks, more attention is paid to nodes with a small number of connections. For super...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/55G06K9/62
Inventor 张勇袁帅王臻郭帅郭佳敏
Owner AGRICULTURAL BANK OF CHINA
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