Aspect-level text sentiment conversion method based on multi-task learning

A multi-task learning and aspect technology, which is applied in the field of aspect-level text sentiment conversion based on multi-task learning, can solve problems such as unsatisfactory effects, and achieve the effect of improving the effect.

Active Publication Date: 2019-08-02
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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Problems solved by technology

However, the existing technologies usually only have document-level emotion conversion, and cannot effectively perform aspect-level text emotion conversion. In addition, the existing text emotion conversion methods only focus on the success rate of emotion conversion, and the effect on content preservation far from ideal

Method used

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  • Aspect-level text sentiment conversion method based on multi-task learning
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  • Aspect-level text sentiment conversion method based on multi-task learning

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[0041] In order to make the purpose, technical solution, design method and advantages of the present invention clearer, the present invention will be further described in detail through specific embodiments in conjunction with the accompanying drawings. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0042] In all examples shown and discussed herein, any specific values ​​should be construed as exemplary only, and not as limitations. Therefore, other instances of the exemplary embodiment may have different values.

[0043] Techniques, methods and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, such techniques, methods and devices should be considered part of the description.

[0044] The embodiment of the present invention provides an aspect-level text emotion conversion method. For a sentence with multi...

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Abstract

The invention provides an aspect-level text sentiment conversion method based on multi-task learning. The method comprises the steps that for a text containing multiple aspect emotion expressions, anaspect-level text conversion learning task is constructed, and an aspect-level emotion classification learning task is constructed; and the aspect-level text conversion learning task is taken as a main task, the aspect-level emotion classification learning task is taken as an auxiliary task, and text emotion conversion of the aspect level is realized through joint training of the main task and theauxiliary task. By means of the method, text sentiment conversion of the aspect level can be effectively achieved, and the content storage effect is improved.

Description

technical field [0001] The invention relates to the technical field of natural language processing, in particular to an aspect-level text emotion conversion method based on multi-task learning. Background technique [0002] Text sentiment conversion refers to transforming the sentiment of the entire text into the opposite sentiment, for example, converting a positive sentiment to a negative sentiment while keeping the sentiment-irrelevant parts unchanged. Text sentiment conversion has a very wide range of application scenarios, such as news rewriting, comment attitude change, etc. [0003] In actual situations, a piece of text often has multiple aspects, and the emotion expressed for each aspect is different, so it is particularly important to perform aspect-level text emotion conversion. However, the existing technologies usually only have document-level emotion conversion, and cannot effectively perform aspect-level text emotion conversion. In addition, the existing text ...

Claims

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Application Information

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IPC IPC(8): G06F16/35G06K9/62
CPCG06F16/35G06F18/2415G06F18/214
Inventor 杨敏曲强陈磊姜青山
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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