Text sentiment classification method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of natural language processing and machine learning, in particular to a text sentiment classification method and device, electronic equipment and a storagemedium. The method comprises the steps: obtaining a to-be-classified target text, processing the target text, and obtaining a word vector sequence of the target text; processing the word vector sequence by using a pre-trained semantic coding model to obtain a word semantic vector sequence corresponding to the word vector sequence and a semantic vector of the target text; inputting the word vectorsequence, the word meaning vector sequence and the semantic vector into a pre-trained sentiment generation model to obtain a sentiment vector of the target text, wherein the sentiment generation model is an attention-based neural network model; inputting the semantic vector and the sentiment vector into a pre-trained sentiment classification model to obtain a sentiment classification result of the target text. According to the method, dynamically generated emotion vectors are introduced, and therefore the emotion classification accuracy is improved.

Description

technical field [0001] The invention relates to the technical fields of natural language processing and machine learning, in particular to a text emotion classification method, device, electronic equipment and storage medium. Background technique [0002] With the development of Internet technology, there are more and more network products. In the process of using network products or after using network products, users usually input network texts expressing their own needs or opinions, such as inputting problems to be solved in intelligent customer service or voice assistants, or posting comments about the specific service after using a certain service. service reviews, etc. Since the network text contains rich emotional information, which corresponds to the corresponding psychological state of the user, by performing emotional analysis on the network text input by the user to determine its emotional category, an appropriate processing strategy can be determined according t...

AI Technical Summary

Problems solved by technology

Existing sentiment classification methods need to rely on external sentiment lexicons or domain knowledge in the process of training classification models, which may cause mismatch problems due to inconsistent labels or poor accuracy of sentiment classification due to insufficient dictionary coverage. question

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