Construction method and device of fine-grained emotion analysis model and readable storage medium

Abstract

The invention discloses a construction method and device of a fine-grained emotion analysis model and a readable storage medium. According to the method, class sequence rules are utilized to extract attribute words and emotion words in a process of fine-grained sentiment analysis, thus accuracy of attribute word and emotion word extraction is improved, the mined class sequence rules are enabled tochange with changes of text which is of the applied field and to be used for training, generalization ability of the constructed fine-grained emotion analysis model is improved, and the constructed fine-grained emotion analysis model is enabled to have good scalability; and the problem of long-distance dependence between emotion words and attribute words is solved through the class sequence rules, that is, the problem of long-distance dependence between evaluation objects and evaluation words is solved, emotion context information related to the attribute words is extracted through a neural network of an attention mechanism, and fine-grained emotion analysis is realized.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a fine-grained emotion analysis model construction method, device and readable storage medium. Background technique [0002] Fine-grained sentiment analysis, also known as attribute-level sentiment analysis, belongs to a category of text sentiment analysis. This analysis is generally based on the sentiment judgment of the attribute features in the comment text. Compared with article-level or sentence-level sentiment analysis, fine-grained sentiment analysis can more specifically and clearly target the relevant attribute characteristics of products for sentiment recognition, and the obtained analysis results provide more detailed evaluation information, so it is more meaningful and value. [0003] The first step of fine-grained sentiment analysis is to extract evaluation objects. Evaluation object extraction is to obtain product attributes that consumers care about from...

AI Technical Summary

Problems solved by technology

[0004] The main purpose of the present invention is to provide a fine-grained sentiment analysis model construction method, equipment and readable storage medium, aiming to solve the problem of poor scalability, weak generalization ability, and inability to Solve the technical problem of long-distance dependence between evaluation words and evaluation objects

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