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Emotion analysis method and device fused with emotion dictionary

A technology of sentiment dictionary and sentiment analysis, applied in text database clustering/classification, special data processing application, unstructured text data retrieval, etc.

Pending Publication Date: 2021-05-28
INDUSTRIAL AND COMMERCIAL BANK OF CHINA
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  • Application Information

AI Technical Summary

Problems solved by technology

[0003] This application provides a sentiment analysis method and device that integrates a sentiment dictionary to at least solve the problem of how to obtain sentiment classification results without labeling the data in the case of a small amount of open source labeling data

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  • Emotion analysis method and device fused with emotion dictionary
  • Emotion analysis method and device fused with emotion dictionary
  • Emotion analysis method and device fused with emotion dictionary

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Embodiment Construction

[0045] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0046] At present, most of the open source labeling data for sentiment classification comes from product reviews and service reviews of Internet companies, and there are few training sample data for news in the financial field. Therefore, higher requirements are put forward for the sentiment analysis model of financial news. In order to obtain better The result of emotion classification requires manual labeling of part of the data as a training data set, result...

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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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Application Information

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IPC IPC(8): G06F16/35G06F16/36
CPCG06F16/35G06F16/374
Inventor 孔繁爽李策江林格
Owner INDUSTRIAL AND COMMERCIAL BANK OF CHINA
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