System and method for text classification

Abstract

The invention relates to a system and method for text classification. The system comprises the steps that an initialization module reads a text, vectorization is conducted to sentences in the text, and a two-dimensional matrix vector is generated; a first extraction module conducts convolution and pool processing to the two-dimensional matrix vector, and multiple first matrix vectors are generated; the second extraction module conducts dot multiplication between the multiple first matrix vectors and an attention matrix respectively, and multiple second matrix vectors are generated; a comprehensive representation module conducts convolution to each matrix vector, so each second matrix vector is correspondingly converted into a first-dimensional vector matrix; and a classification module inputs the multiple first-dimensional vector matrixes into Fully Contact Layer for processing respectively, inputs output values to a softmax classifier, and the softmax classifier converts matrix values into probability distributions of corresponding classes, so that the text classification is completed. According to the invention, only a few of parameters are used; a network model can be converged rapidly; representation information of a text depth is extracted; and thus, accuracy for the text classification can be increased.

Description

technical field [0001] The invention relates to a text classification system and method. Background technique [0002] With the widespread use of the Internet and mobile terminals, users can easily express their emotions, opinions and comments on the Internet and mobile platforms, resulting in massive text information resources. Therefore, text classification has become very important, and text classification has become more and more important. hot research focus. [0003] In recent years, with the increasing application of CNN (Convolutional Neural Network, convolutional neural network) and attention mechanism (Attention mechanism) in the field of natural language processing, fruitful results have been achieved. The existing technology has deep network measurement layers, many parameters, too long iteration time, and shallow network cannot fully extract effective features. This method uses a shallow CNN network combined with an attention mechanism, which can effectively e...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a text classification system and method. The technical problem to be solved is: how to solve the problem of deep network measurement layers, many parameters, too long iteration time, and shallow network cannot fully extract effective features.

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