Transaction information identification method and system based on graph neural network, and medium
The invention discloses a transaction information identification method and system based on a graph neural network, and a medium. The method comprises the steps of obtaining a to-be-identified text; performing feature extraction and label prediction on the to-be-recognized text to obtain a labeling...
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creator | YU GUANGBO GAN WEICHAO ZHOU JINGYU ZOU HONGYUE LIN YUANPING |
description | The invention discloses a transaction information identification method and system based on a graph neural network, and a medium. The method comprises the steps of obtaining a to-be-identified text; performing feature extraction and label prediction on the to-be-recognized text to obtain a labeling result of entity elements in the to-be-recognized text; constructing a corresponding entity relation graph according to the labeling result of the entity elements; performing feature learning on the entity relation graph through a graph attention network and then outputting entity node feature vectors; and performing feature multi-classification on the entity node feature vector, and outputting a transaction element category of each entity node. According to the method, the relation between the entity elements is subjected to feature learning and classification by constructing the entity relation graph, the transaction mechanism category of each entity is recognized, classification judgment can be more accurately c |
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The method comprises the steps of obtaining a to-be-identified text; performing feature extraction and label prediction on the to-be-recognized text to obtain a labeling result of entity elements in the to-be-recognized text; constructing a corresponding entity relation graph according to the labeling result of the entity elements; performing feature learning on the entity relation graph through a graph attention network and then outputting entity node feature vectors; and performing feature multi-classification on the entity node feature vector, and outputting a transaction element category of each entity node. 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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
title | Transaction information identification method and system based on graph neural network, and medium |
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