Text semantic recognition method and device, computer equipment and storage medium

Abstract

The invention relates to the technical field of natural language processing, and provides a text semantic recognition method and device, computer equipment and a storage medium. The method comprises the steps of determining text characters contained in a target text and text segmented words to which each text character belongs; calculating character vectors corresponding to the text characters andword vectors corresponding to the text segmented words; splicing the word vector of each text character with the word vector of the text segmented word to which the text character belongs to obtain aspliced vector of the corresponding text character; inputting the word vector into a first neural network layer to obtain a first feature vector, and inputting the splicing vector into the first neural network layer to obtain a second feature vector; and inputting a comprehensive feature vector obtained by splicing the first feature vector and the second feature vector into a second neural network layer to obtain a semantic type of the target text. By adopting the method, the accuracy of text semantic recognition can be improved.

Description

technical field [0001] The present application relates to the technical field of natural language processing, in particular to a text semantic recognition method, device, computer equipment and storage medium. Background technique [0002] Based on the needs of intelligent customer service and instant messaging, it is often necessary to perform semantic recognition on text data. With the development of the Internet, text semantic recognition technology has been more and more widely used, especially in the field of intelligent customer service. For example, in the field of intelligent customer service, in order to accurately answer the text data entered by the user, the intelligent customer service usually needs to perform semantic recognition on the text data entered by the user, and judge the true meaning expressed by the text data, so as to accurately and quickly answer the questions raised by the user. Another example is in the field of instant messaging, in order to pre...

AI Technical Summary

Problems solved by technology

[0003] At present, most text semantic analysis technologies are implemented using keyword matching methods. In this way, if keywords that are not recorded in the keyword database appear in the text data, their semantics cannot be accurately recognized, that is, the accuracy of text semantic recognition is limited by key words. Word coverage, resulting in lower accuracy of text semantic recognition

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