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A view-level text sentiment classification method and system integrating external knowledge and interactive attention mechanism

A technology of external knowledge and sentiment classification, applied in the field of text processing, can solve the problem of lack of different meanings of words

Active Publication Date: 2022-06-03
FUZHOU UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Although this type of method can better handle complex sentences, it lacks consideration of the different meanings of words in the text in different contexts.

Method used

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  • A view-level text sentiment classification method and system integrating external knowledge and interactive attention mechanism
  • A view-level text sentiment classification method and system integrating external knowledge and interactive attention mechanism
  • A view-level text sentiment classification method and system integrating external knowledge and interactive attention mechanism

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Embodiment Construction

[0079] The present invention will be further described below in conjunction with the accompanying drawings and examples.

[0080] It should be noted that the following detailed description is exemplary and intended to provide further explanation for the application. unless otherwise

[0081] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting

[0082] As shown in FIG. 3, this embodiment provides a perspective-level text that integrates external knowledge and an interactive attention mechanism

[0084] First, by the Glove model, the text data after the word segmentation process is converted into a vector representation;

[0085] Then use BiLSTM to extract semantic features from the text; solve the problem that the long short-term memory network (LSTM) cannot encode

[0086]

[0087]

[0089] Since a word may have different meanings in different contexts, especially when focusing on emoti...

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Abstract

The present invention relates to a view-level text emotion classification method and system that integrates external knowledge and an interactive attention mechanism, including the steps of: constructing text sequence content with external knowledge, and introducing sentinel vectors to improve the misleading effect of external knowledge on the model; constructing Memory content with interactive information and location information; construct a multi-layer attention representation of memory content, and combine the attention results with the gated recurrent unit nonlinearly to finally form a view-level text emotional feature representation; use the classification function to get the final text sentiment classification results. The invention can characterize the view-level text, extract semantic features from the text through BiLSTM, and then obtain the final classification result through a multi-layer attention mechanism.

Description

A Perspective-Level Text Sentiment Classification Based on External Knowledge and Interactive Attention Mechanism method and system technical field The present invention relates to the technical field of text processing, especially a kind of visual fusion of external knowledge and interactive attention mechanism. Corner-level text sentiment classification method and system. Background technique [0002] Perspective-level text sentiment analysis aims to study the sentiment polarity (such as positive, negative, negative, etc.) polar and neutral). As a fine-grained task in sentiment analysis, perspective-level text sentiment analysis can provide more Sentence-level sentiment analysis is more comprehensive and in-depth analysis, which can be widely used in product pricing, competitive intelligence, stock market forecasting It has important theoretical research significance and practical application value. As shown in Figure 1, there are two perspective words "salmon" i...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/35G06F40/247G06F40/30G06N3/04
CPCG06F16/35G06F40/247G06F40/30G06N3/044G06N3/045
Inventor 廖祥文曾梦美邓立明陈甘霖陈开志
Owner FUZHOU UNIV
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