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A Multimodal Sentiment Analysis Method Based on Quantum Theory

A technology of sentiment analysis and quantum theory, applied in character and pattern recognition, special data processing applications, text database clustering/classification, etc., can solve the problems of not considering and modeling interference effects, and not having multi-modal sentiment analysis, etc. To achieve the effect of improving the accuracy

Active Publication Date: 2020-03-06
TIANJIN UNIV
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AI Technical Summary

Problems solved by technology

The existing multimodal sentiment analysis technology mainly revolves around extracting multimodal features and training excellent classifiers. It does not look at multimodal sentiment analysis from the cognitive level, let alone consider and model the interference between such modalities. effect

Method used

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  • A Multimodal Sentiment Analysis Method Based on Quantum Theory
  • A Multimodal Sentiment Analysis Method Based on Quantum Theory
  • A Multimodal Sentiment Analysis Method Based on Quantum Theory

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Embodiment Construction

[0035] The technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings, but the protection scope of the present invention is not limited to the following description. figure 1 It shows the flow of the multimodal sentiment analysis method based on quantum theory proposed by this method; figure 2 A flowchart showing the multimodal quantum representation model; image 3 An analogy diagram showing multimodal sentiment analysis and quantum interference; Figure 4 The comparison results of sentiment classification between the final different algorithms are shown. Specific steps are as follows:

[0036] (1): Based on the famous emotional dictionary SentiWordNet, select 127 keywords containing positive and negative emotions to form an emotional vocabulary, in which the number of positive emotional words is 62, such as happy (happy), smiling (smiling), etc., negative The number of emotional words is 65, such as...

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Abstract

The invention relates to a multi-modal sentiment analysis method based on quantum theory, comprising: constructing a multi-modal emotional corpus; selecting a training set and a test set, and preprocessing the training set and the test set respectively; Extract the respective features of the text and images, and construct the text density matrix and image density matrix respectively; input the text density matrix and image density matrix in the training set into the random forest classifier, and train the text sentiment classification model and image sentiment classification model; Input the text matrix and image matrix of the test set corpus into the text and image emotion classification model, classify the emotion categories, and calculate the respective prediction probabilities; use the multi-modal decision fusion method to fuse the text prediction probability and image prediction probability weightedly, and finally calculate The classification accuracy of each multimodal sample is obtained.

Description

technical field [0001] The invention relates to the technical field of multimodal emotion classification, in particular to a multimodal emotion analysis method. Background technique [0002] With the rapid development of the Internet and social networks, more and more users like to post comments and share their opinions on social platforms (such as Weibo, Facebook, Flickr, etc.), which has become one of the main sources of information for users in their daily lives. one. Different from the previous information transmission only through text form, users are more and more inclined to use multiple media forms (such as text plus image, text plus song, text plus video, etc.) to express their emotions together. Compared with single modality, multimodality can express more accurate and intuitive emotional information. On the other hand, the importance of analyzing multimodal subjectivity documents has been recognized by all walks of life in society. It can help product manufactur...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62G06F16/35G06F16/36
CPCG06F16/35G06F16/36G06V40/174G06V40/172G06F18/23213G06F18/214
Inventor 张亚洲宋大为
Owner TIANJIN UNIV
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