Text emotion classification method and device, electronic device and readable storage medium

Abstract

The embodiment of the invention provides a text emotion classification method and device, an electronic device and a readable storage medium. The method comprises the steps of obtaining a target wordvector corresponding to a target keyword in a to-be-classified target text; extracting the syntactic features of the target word vector through a first Bi-LSTM layer, and outputting a target syntacticfeature vector representing the syntactic features; extracting the semantic features of the target syntax feature vector through a second Bi-LSTM layer, and outputting a target semantic feature vector representing the semantic features; and determining an emotion category corresponding to the target text based on the target word vector, the target syntax feature vector and the target semantic feature vector through a classification layer. Due to the fact that the syntactic features and the semantic features of the target keywords can be extracted, the obtained information can be more comprehensive, the intrinsic meaning of the target text can be more deeply understood, and the accuracy of the classification result can be effectively improved.

Description

technical field [0001] The present application relates to the technical field of language understanding, and in particular, to a text emotion classification method, apparatus, electronic device, and readable storage medium. Background technique [0002] With the rapid development of Internet technology, more and more users like to post their opinions, attitudes and opinions on social platforms, thus generating a large number of users on the Internet with valuable text information on hot events and products. These textual information contains rich emotional colors and emotional tendencies of users. The purpose of sentiment analysis is to automatically extract and classify users' subjective emotional information from texts to understand the public's views on an event or product. [0003] At present, machine learning methods are generally used to recognize sentiment categories of texts, which usually input the relevant features of the extracted texts into the classifier, and th...

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Problems solved by technology

[0004] In view of this, the purpose of the embodiments of the present application is to provide a text sentiment classification method, device, elec

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