Emotion classification method based on a tensor fusion mode

Abstract

The invention relates to an emotion classification method based on a tensor fusion mode. The method comprises the steps of (1) data preprocessing; (2) training word vectors; (3) modeling specific tasks; the context information and the semantic information of each sentence are coded through bidirectional LSTM, and the feature vector representation of each sentence is obtained through the effect ofeach layer of network; and (4) tensor fusion: fusing the three feature vectors output by the model by adopting a tensor fusion mode, obtaining an optimal and comprehensive feature representation through information fusion, and then sending the feature vectors formed after fusion to a classifier for emotion classification. (5) training model. Any feature does not need to be extracted manually, themodel does not need to preprocess data by means of an additional natural language processing tool, meanwhile, emotion classification does not need to be conducted by recognizing current words in advance, the algorithm is simple and clear, and the effect is obvious.

Description

technical field [0001] The invention relates to a method for emotional classification based on tensor fusion, and belongs to the technical field of natural language processing. Background technique [0002] With the development of the current era, the era of network information has rapidly affected people's lives at an unprecedented speed. At the same time, social media also presents a variety of forms. Online media such as forums, blogs, and microblogs develop rapidly, and the participation of online users continues to increase, which has also brought about tremendous changes in the way the Internet is used. Users no longer just passively acquire network knowledge, but become more active creators of network information. Such changes have resulted in the emergence of a large number of subjective information in various forms used to express user emotions, emotions and opinions in the network media. , and text is one of the most important forms of expression. For these subje...

AI Technical Summary

Problems solved by technology

However, there may be multiple emotional tendencies in some complex texts, and how to get a correct sentiment classification result has become the difficulty of text sentiment classification.

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