Classification model training method and device, electronic equipment and storage medium

A classification model and classification result technology, applied in the information field, can solve the problem of low training efficiency of heterogeneous graph classification model

Pending Publication Date: 2021-06-15
BEIJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0004] The purpose of the embodiments of the present application is to provide a classification model training method, device, electronic equipment and storage medium to solve the problem of low training efficiency of heterogeneous graph classification models

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  • Classification model training method and device, electronic equipment and storage medium
  • Classification model training method and device, electronic equipment and storage medium
  • Classification model training method and device, electronic equipment and storage medium

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Embodiment Construction

[0063] The following will clearly and completely describe the technical solutions in the embodiments of the application with reference to the drawings in the embodiments of the application. Apparently, the described embodiments are only some of the embodiments of the application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art based on this application belong to the scope of protection of this application.

[0064] In the first aspect of the embodiment of the present application, a training method of a classification model is firstly provided, which is applied to a classification model to be trained, and the classification model to be trained includes a heterogeneous graph structure learning network to be trained and a graph neural network to be trained , the above methods include:

[0065] Obtain the characteristics of each node and each element path in the sample heterogeneous graph, wherei...

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Abstract

The embodiment of the invention provides a classification model training method and device, electronic equipment and a storage medium, which are applied to the technical field of information, and the method comprises the steps of generating a sample heterogeneous graph according to a sample heterogeneous graph, extracting a semantic graph, generating a relation sub-graph, obtaining a classification result of a to-be-classified target according to the relation sub-graph, calculating the current loss, and adjusting the parameters of the to-be-trained heterogeneous graph structure learning network and the to-be-trained graph neural network at the same time according to the current loss, so that the model training efficiency can be improved.

Description

technical field [0001] The present application relates to the field of information technology, in particular to a classification model training method, device, electronic equipment and storage medium. Background technique [0002] A heterogeneous graph refers to a graph containing many different types of nodes and relationships. In reality, heterogeneous graphs can often better reflect the relationship between objects to be classified. For example, when classifying movies and actors, the same actor may appear in multiple movies, and the same movie may include multiple actors. [0003] However, when training the classification model of the heterogeneous graph of the object to be classified, the heterogeneous graph is directly identified and the object to be classified is classified, because the relationship between the nodes in the heterogeneous graph is often complicated, and the observed The obtained heterogeneous graph structure often cannot reflect this complex relations...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/22G06F18/25G06F18/241G06F18/214
Inventor 王啸石川赵健安
Owner BEIJING UNIV OF POSTS & TELECOMM
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