Text processing method, electronic equipment and storage medium

Abstract

Embodiments of the invention provide a text processing method, electronic equipment and a storage medium. The method comprises the steps of obtaining a to-be-processed text and a label corresponding to the text; determining a plurality of candidate event sentences from event sentences contained in the text, the event sentences being sentences containing event trigger words and named entities; respectively calculating the similarity between the plurality of candidate event sentences and the label; and taking the candidate event sentences of which the similarity meets a preset similarity condition in the plurality of candidate event sentences as topic sentences corresponding to the text. In this way, the determined topic sentences are high in accuracy, and the text can be described simply and accurately.

Description

technical field [0001] The present application relates to the technical field of computers, and in particular to a text processing method, electronic equipment and storage media. Background technique [0002] With the continuous development of computer technology and the Internet, more and more information is presented to users in the form of electronic text, and the Internet has become the main source for people to obtain information. For example, people can obtain news information from social networking sites. [0003] However, with the rapid increase of texts in the Internet, it is difficult for people to quickly and accurately obtain the information they are interested in from the numerous texts. At present, in order to facilitate users to obtain information from a large number of texts, the topic sentence used to describe the text is mainly determined by the Term Frequency-Inverse Document Frequency (TF-IDF) method. However, the method determined The accuracy of the to...

AI Technical Summary

Problems solved by technology

[0003] However, with the rapid increase of texts in the Internet, it is difficult for people to quickly and accurately obtain the information they are interested in from numerous texts

At present, in order to facilitate users to obtain information from a large number of texts, the topic sentence used to describe the text is mainly determined by the Term Frequency-Inverse Document Frequency (TF-IDF) method. However, the method determined The accuracy of the topic sentence is low, and it cannot describe the text concisely and accurately.

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