attention CNNs and CCR-based text sentiment analysis method

Abstract

The invention discloses an attention CNNs and CCR-based text sentiment analysis method and belongs to the field of natural language processing. The method comprises the following steps of 1, training a semantic word vector and a sentiment word vector by utilizing original text data and performing dictionary word vector establishment by utilizing a collected sentiment dictionary; 2, capturing context semantics of words by utilizing a long-short-term memory (LSTM) network to eliminate ambiguity; 3, extracting local features of a text in combination with convolution kernels with different filtering lengths by utilizing a convolutional neural network; 4, extracting global features by utilizing three different attention mechanisms; 5, performing artificial feature extraction on the original text data; 6, training a multimodal uniform regression target function by utilizing the local features, the global features and artificial features; and 7, performing sentiment polarity prediction by utilizing a multimodal uniform regression prediction method. Compared with a method adopting a single word vector, a method only extracting the local features of the text, or the like, the text sentiment analysis method can further improve the sentiment classification precision.

Description

technical field [0001] The invention is a method for analyzing text emotion, which belongs to the field of natural language processing. Background technique [0002] With the rise of social platforms such as Twitter, Facebook, and Weibo, and e-commerce platforms such as Amazon and Taobao, commentary text resources on the Internet are increasing day by day. Faced with a large number of unstructured comment texts from Weibo and forums, it is urgent to analyze and judge the emotional tendency expressed in the text through natural language processing technology. For example, identifying the emotional information of product attributes from comments can provide decision support for merchants and other users; in public opinion monitoring, the government can keep abreast of people's attitudes towards emergencies and social phenomena, and guide public opinion trends. The vast majority of traditional sentiment analysis uses the combination of traditional NLP features and machine lear...

AI Technical Summary

Problems solved by technology

[0004] The present invention proposes a text sentiment analysis method based on attention CNNs combined with convolutional neural network and CCR multi-mode consistent regression. By analyzing the emotional polarity of the word segmentation text, it solves the problem of only extracting and analyzing the local features of the text, resulting in the lack of global Features, the extracted features are single, not enough to reflect the emotional polarity of the text

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