Multi-modal sentiment analysis method based on quantum theory

Abstract

The invention relates to a multi-modal sentiment analysis method based on the quantum theory. The method comprises the steps of constructing a multi-modal sentiment corpus set; selecting a training set and a test set, and pre-processing the training set and the test set respectively; extracting respective characteristics from pre-processed texts and images, and constructing text density matrices and image density matrices respectively; inputting the text density matrix and the image density matrix in the training set into a random forest classifier to obtain a text sentiment classification model and an image sentiment classification model; inputting the text matrix and image matrix of the test set corpus into the text and image sentiment classification models to classify the sentiment categories and calculating respective prediction probabilities thereof; and subjecting the text prediction probabilities and the image prediction probabilities to weighted fusion by using a multi-modal decision-making fusion method to finally calculate the classification accuracy of each multi-modal sample.

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...

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

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