Automatic text classification method based on BERT and feature fusion

A technology of automatic classification and feature fusion, applied in the field of supervised text classification and deep learning, can solve the problems of word vector or word vector change, single information coverage, etc., and achieve the effect of improving accuracy and coding ability.
CN110413785AActive Publication Date: 2019-11-05HUAIYIN INSTITUTE OF TECHNOLOGY
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
HUAIYIN INSTITUTE OF TECHNOLOGY
Publication Date
2019-11-05

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Abstract

The invention discloses an automatic text classification method based on BERT and feature fusion. The method comprises the following steps: firstly, cleaning text data, realizing conversion from a text to a dynamic word vector through BERT, extracting features of the text by utilizing CNN and BiLSTM, and respectively transmitting a word vector sequence output by the BERT to a CNN network and a BiLSTM network; then, splicing the output of a CNN network and the output of a BiLSTM network together, carrying out feature fusion, and finally, outputting a final prediction probability vector througha full connection layer and a softmax layer. The method is suitable for the general supervised text label prediction problem, and can effectively improve the prediction accuracy of the text data labels with prominent sequence information and local features.
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Description

technical field

[0001] The invention relates to the field of supervised text classification and deep learning, in particular to an automatic text classification method based on BERT and feature fusion. Background technique

[0002] With the rapid increase of online text information data on the Internet, text classification plays a vital role in information processing. It is a key technology for processing large-scale text information and promotes the development of information processing in the direction of automation. Text classification is to automatically classify and mark text data according to a certain classification system or standard. It belongs to an automatic classification based on the classification system. Building a reasonable pre-trained language model and a downstream network structure can effectively solve the text classification problem, thereby improving the accuracy of the predicted label.

[0003] In the traditional text classification methods, most of...

Claims

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