Text data labeling method, device, electronic equipment and storage medium

Abstract

The present application discloses a text data tagging method, device, electronic device and storage medium, by using a tag prediction model to generate a first candidate tag of text data, and using a word vector model to generate a second candidate tag for a text title of the text data, Then calculate the correlation between the first candidate tag and the second candidate tag with respect to the text data, and extract the candidate tags whose correlation exceeds the corresponding correlation threshold as the machine-labeled data of the text data. This application can improve the accuracy and comprehensiveness of text data labeling.

Description

Text data annotation method, device, electronic device and storage medium technical field The application belongs to artificial intelligence technical field, specifically, relate to a kind of text data labeling method, device, computer Subdevices and storage media. Background technique [0002] Usually, on some text information exchange platforms, there will be a large number of texts with creative content such as blog posts and questions and answers. Data, in order to facilitate user navigation, retrieval and classification, the content created under the platform will be tagged. For the labeling processing of text data, algorithms such as artificial intelligence or machine learning are generally used to Can label, such as using TextCNN model, BERT model, etc. to automatically label text data. These notation methods are The accuracy of the labeling results of this data is also getting higher and higher, but there are still labels that produce obvious errors for some...

AI Technical Summary

Problems solved by technology

The accuracy of these annotation methods for text data annotation results is getting higher and higher, but there are still some obvious errors in the annotation of some text data.

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