Text data processing method, device, electronic device and storage medium

Abstract

The embodiment of the present application discloses a text data processing method, device, electronic equipment, and storage medium. The method includes: obtaining text data to be classified, extracting aspect feature words from it, and obtaining text word vector representation and aspect features of the text data to be classified The aspect feature word vector representation of the word is input into the target neural network respectively to obtain the meaning of the first hidden layer represented by the text word vector and the second hidden layer meaning represented by the aspect feature word vector. Based on the meaning of the first hidden layer and the second hidden layer According to the target classification features of the aspect feature words, the predicted emotional polarity of the aspect feature words is obtained, and according to the predicted emotional polarity, the sentiment classification is performed on the classified text data to obtain the corresponding aspect feature words. Sentiment classification results and display. The application realizes accurate judgment of the emotional polarity of aspect feature words based on attention mechanism and neural network.

Description

Text data processing method, device, electronic device and storage medium technical field The application relates to the technical field of natural language processing, more specifically, to a text data processing method, a device devices, electronic equipment and storage media. Background technique Sentiment analysis is a basic task in natural language processing, which can be used to mine users' opinions and conduct statistical Data analysis, public opinion monitoring and other tasks. Sentiment analysis can be divided into the extraction of emotional information, the classification of emotional information and the emotional information. Information retrieval and summarization. Among them, sentiment classification refers to classifying texts into positive and negative groups according to the meaning and emotional information expressed by the text Two or more types of positive or pejorative meanings are the divisions of the inclinations, opinions and attitudes of t...

AI Technical Summary

Problems solved by technology

However, a sentence may involve many different emotions for different aspects. At present, there are limitations in the sentiment classification of texts containing multiple emotions or multiple aspects.

Images