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Neural network system and method for analyzing relational network diagram

A relational network, neural network technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as failure to achieve analytical results

Active Publication Date: 2019-07-12
ADVANCED NEW TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Under such circumstances, the graph neural network GNN cannot achieve the expected analysis effect

Method used

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  • Neural network system and method for analyzing relational network diagram
  • Neural network system and method for analyzing relational network diagram
  • Neural network system and method for analyzing relational network diagram

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Embodiment approach

[0061] According to an implementation manner of this specification, the deep neural network DNN is used as a branch of the neural network system of an embodiment. After the feature vector of the node is extracted by the feature extraction layer 21, the feature vector is provided to the input layer of the deep neural network DNN 22, processed through the hidden layer, and the processed result is output through the output layer of the DNN. For simplicity of description, the processing process of the feature vector by the DNN hidden layer is called the first processing, and the processing result output by the DNN output layer is called the first output.

[0062] It should be noted that descriptions such as "first" and "second" herein are only used to distinguish similar concepts, and for the sake of simplicity and clarity of description, and do not have a limiting role in other aspects such as order.

[0063] On the other hand, the node feature vectors extracted by the feature ex...

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Abstract

The embodiment of the invention provides a neural network system and method executed by a computer and used for analyzing a relational network diagram, and the neural network system comprises a feature extraction layer which is used for extracting feature vectors of nodes in the relational network diagram; a deep neural network used for carrying out first processing on the feature vectors to obtain first output; a diagram neural network used for combining the adjacency information of the relational network diagram and carrying out second processing on the feature vectors to obtain second output, wherein the adjacency information being used for representing a connection relation between nodes contained in the relation network diagram; and a fusion layer used for fusing the first output andthe second output and outputting a prediction result for the node based on a fusion result.

Description

technical field [0001] One or more embodiments of this specification relate to a neural network system executed by a computer, and in particular to a neural network system and method for analyzing a relational network graph. Background technique [0002] Graphs are a powerful tool for modeling relational data. Therefore, at present, data with associated relationships are often expressed and modeled in the form of graphs. On the other hand, a graph-based neural network using deep learning methods, Graph Neural Network (Graph Neural Network, Graph NN or GNN), is proposed for learning graph information. The graph neural network GNN can effectively use the information transmission on the graph and integrate the feature information of nodes or edges to complete machine learning tasks such as classification or regression of nodes or edges on the graph. [0003] However, in real business scenarios, especially in the initial stage of business, such as the stage of inviting new user...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06N3/08G06F16/28
CPCG06N3/084G06F16/288G06N3/045
Inventor 常晓夫宋乐
Owner ADVANCED NEW TECH CO LTD
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