A Chinese text sentiment classification method based on multi-core two-layer convolutional neural network

Abstract

The invention discloses a Chinese text emotion classification method based on a multi-core double-layer convolutional neural network, comprising: acquiring a Chinese text data set, and preprocessing the Chinese text data set; The preprocessed Chinese text data set is subjected to feature extraction to obtain several different word vector matrices; a Chinese text sentiment classifier is constructed based on a multi-core double-layer convolutional neural network, and several different word vector matrices extracted are input To the Chinese text emotion classifier, the training of the Chinese text emotion classifier is completed; the trained Chinese text emotion classifier is used to perform emotion classification on Chinese text. The present invention can retain the salient features of Chinese text, reduce the feature dimension, avoid the problems of too abstract feature extraction and information loss, solve the problem of insufficient extracted feature information, and realize fast and accurate classification of Chinese text emotions.

Description

technical field [0001] The invention relates to the technical field of Chinese text emotion classification, in particular to a Chinese text emotion classification method based on a multi-core double-layer convolutional neural network. Background technique [0002] With the rapid development of the Internet, especially the advent of the Web 2.0 era, network information dissemination has developed from one-way information release to dynamic information interaction. Users are no longer just readers of network content, but also producers of network content. Network communication platforms such as forums, Weibo, WeChat, and e-commerce reviews continue to emerge, and people are becoming more and more accustomed to posting subjective remarks on the Internet to express their views on events and policies they are concerned about or the goods and services they purchase. and views. Data rich in emotional information generated by a large number of users on the Internet provides new opp...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a Chinese text emotion classification method based on a multi-core double-layer convolutional neural network, to solve the problems of the prior art, to retain the salient features of the Chinese text, reduce the feature dimension, and avoid feature extraction that is too abstract and The problem of information loss has also solved the problem of insufficient feature information extraction through a variety of different convolution kernels. It has the advantages of good processing of discrete data, latent semantic analysis, consideration of word polysemy, and suitable for processing large-scale data. Fast and Accurate Classification of Sentiment in Chinese Text

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