Emotion analysis method and device fused with emotion dictionary

Abstract

The invention provides a sentiment analysis method and device fused with a sentiment dictionary, which can be applied to the field of artificial intelligence. The method comprises the following steps: inputting an obtained sentence in a source field and an obtained sentence in a target field into a pre-generated encoder to obtain a source field sentence word vector and a target field sentence word vector; inputting the source field word vector and the target field sentence word vector into a sentence vector encoder to respectively obtain source field sentence representation and target field sentence representation; and obtaining a sentiment classification result of the target domain by using the source domain sentence representation and the target domain sentence representation. According to the method, sentiment words are taken as prediction targets, corpora of a source domain and a target domain are jointly trained through a language model, an encoder capable of extracting sentiment analysis related features is generated, and then feature vectors of texts to be subjected to sentiment classification are generated by using a word encoder; therefore, the technical effect that the available classification result can be obtained by using less or no annotation data is achieved.

Description

technical field

[0001] The present application belongs to the technical field of natural language processing, and in particular, relates to a sentiment analysis method and device integrating a sentiment dictionary. Background technique

[0002] With the wide application of deep learning models in the field of natural language processing, the accuracy of text sentiment analysis results has also been greatly improved. Currently, deep learning models have been used to analyze product reviews and public opinion. In the financial industry, it is of great significance for the bank's credit risk control to judge the public's sentiment index on the legal person by effectively analyzing the current affairs news related to the legal person customer. Sentiment analysis of public opinion of legal person customers can provide auxiliary decision support for banks when monitoring the risk situation of legal person customers. However, at present, most of the open source labeled data for se...

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