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Graph data node classification method and device

A node classification and graph data technology, applied in the field of artificial intelligence, can solve the problem of inability to accurately mine the similarity relationship of nodes, and achieve the effect of improving the accuracy rate

Active Publication Date: 2021-06-18
NAT INNOVATION INST OF DEFENSE TECH PLA ACAD OF MILITARY SCI
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AI Technical Summary

Problems solved by technology

[0015] In view of the problems existing in the prior art, the purpose of the present invention is to solve the problem that the machine learning method for graph data cannot accurately mine the similarity relationship between nodes

Method used

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  • Graph data node classification method and device
  • Graph data node classification method and device
  • Graph data node classification method and device

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Embodiment Construction

[0062] The technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Apparently, the described embodiments are part of the embodiments of the present invention, not all of them. 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.

[0063] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer" etc. The indicated orientation or positional relationship is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the referred device or element must have a specific orientation, or i...

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Abstract

The invention discloses a graph data node classification method and device, and the method comprises the following steps: S1, obtaining graph structure data which comprises feature information and topological structure information; S2, learning hidden layer characterization of the graph nodes in a clustering mode, and constructing an optimization model for the hidden layer characterization of the graph nodes; S3, solving the optimization model to obtain a new representation of the graph node; and S4, executing graph node classification according to the new representation of the node, and constructing a new neural network structure. According to the graph data node classification method and device based on node similarity, the correct rate of graph node classification is greatly improved.

Description

technical field [0001] The invention relates to the field of artificial intelligence, in particular to a machine learning technology for processing graph data, in particular to a graph data node classification method and device based on node similarity. Background technique [0002] The node classification task is to predict which category the category without labels belongs to given the category corresponding to some nodes in the graph. Existing technical methods can be roughly divided into the following categories: [0003] 1. Classification of Probability Relationships [0004] The core idea of ​​the probabilistic relationship classifier is that the label of a node is the mean value of the probabilities of the corresponding labels of its neighbor nodes. First, initialize the distribution probability of nodes that already have labels. The positive example is 1, and the negative example is 0. The probability of nodes without labels is all set to 0.5, and then the probabil...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/04G06N3/08G06F18/23G06F18/241
Inventor 寇广易晓东王之元胡志辉张浩宇
Owner NAT INNOVATION INST OF DEFENSE TECH PLA ACAD OF MILITARY SCI
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