Text classification method based on word sense disambiguation convolutional neural network

Abstract

The invention discloses a text classification method based on a word sense disambiguation convolutional neural network. The method comprises the following steps of configuring an ambiguous word bank with determined word senses; obtaining a related file, extracting text content from the file, and performing word segmentation processing on each statement in the text; determining the part-of-speech of each word in the statement; determining a disambiguation target word; determining the meaning of the target word and performing disambiguation processing; performing word segmentation processing andstop word removal processing on original statements contained in the disambiguated text to obtain target statements corresponding to the original statements; determining the criticality of words in the target statement; determining the criticality of the target statement; sorting the statements according to the criticality of the statements to obtain a target text; and utilizing the trained textclassification model based on the convolutional neural network to classify the target text. According to the method, text classification can be carried out based on the word sense disambiguation convolutional neural network, the text classification method is optimized, the text classification efficiency and the text classification accuracy are improved, and time and labor are saved.

Description

technical field [0001] The invention relates to the technical field of text classification, in particular to a text classification method based on word sense disambiguation convolutional neural network. Background technique [0002] With the increasing development of network media and the increasing number of netizens, a large amount of text data is constantly being generated. How to deal with the huge text data and correctly classify it is an urgent problem to be solved. Text classification uses existing data to train classifiers, and Use this classifier to test documents to determine the category of each document. Correct text classification can enable users to find the information they need faster and browse documents more conveniently. Automatic text classification refers to training text with category marks. That is, train a text classifier, and then use the classifier to test unknown categories of text for recognition; [0003] In the existing technology, text classif...

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Problems solved by technology

[0004] The current text classification method is relatively complex, the efficien

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