Chinese sentiment orientation classification method based on global average pooling convolutional neural network

Abstract

The invention provides a Chinese emotional tendency classification method based on a global average pooling convolutional neural network, which is a technology for analyzing Chinese text collected from a network by a computer. This method constructs a Chinese emotional orientation classification model based on the global average pooling convolutional neural network. The model uses a three-layer channel transformation convolutional layer to extract semantic emotional features, and then the global average pooling layer extracts the features of the convolutional layer. Perform pooling calculations to obtain the confidence values ​​corresponding to each output category, and then output the sentiment classification label by Softmax. In this method, the model parameters are set for multiple trainings, and the model with the highest classification accuracy is selected for Chinese emotional orientation classification. The invention avoids the cumbersome feature engineering in the traditional sentiment analysis, strengthens the ability of the model to extract semantic emotion features, effectively avoids the model over-fitting, and improves the performance of the model sentiment tendency classification.

Description

technical field [0001] The invention belongs to the technical field of natural language processing, relates to a technology for analyzing Chinese texts collected from a network by using a computer, and in particular relates to a classification model oriented to the emotional tendency of Chinese texts, as well as the training of the model and the application of the model to perform text emotional analysis. Methods of propensity classification. Background technique [0002] With the development of the Internet, more and more people tend to express their opinions, express their emotions and express their opinions through the Internet. The vigorous development of various new network platforms such as social networking, e-commerce and self-media has led to the exponential growth of Internet information. For e-commerce merchants, user feedback is an effective means to improve the quality of their own products and services. Sentiment tendency analysis of text is an important mean...

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a Chinese emotional tendency classification method based on the global average pooling convolutional neural network to solve the problems of cumbersome feature engineering of existing emotional classification methods, easy introduction of human factor interference, and limitation of specific tasks, etc.

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