Text generation and evaluation system with emotion tags based on deep learning
A deep learning and evaluation system technology, applied in the field of evaluation system, which can solve the problems of limited development, excessive manual labeling of data, and small amount of calculation.
Pending Publication Date: 2020-11-10
BEIHANG UNIV
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Problems solved by technology
The shallow learning method has a small amount of calculation and is easy to implement, but due to the limitation of the expression ability of complex functions, the generalization ability of complex classification problems is restricted
In order to make up for this defect, artificially constructed features are introduced into this model, such as the use of artificially labeled sentiment dictionaries, syntax and grammatical analysis, etc. Although these methods can effectively improve the accuracy of text sentiment analysis, due to the need for too much Manually labeling data is time-consuming and labor-intensive, and requires certain prior knowledge. Therefore, with the continuous development of the scale of the Internet, the scale of text data continues to expand, which limits the development of these methods.
Method used
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Embodiment 1
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[0071] The experimental results are shown in the table above, where it can be seen intuitively that the control model CNN-Attention is better than the experimental model AEGAN.
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Abstract
The invention relates to a text generation and evaluation system with emotion tags based on deep learning, in particular to a text generation and evaluation system with an emotion label based on deeplearning, which is realized by the following technical scheme: generating a comment introduction model through a data introduction model, and finally scoring and realizing visualization so that high-quality text with emotional colors can be generated. Compared with other existing evaluation systems at present, the invention has the advantages that the quality of the generated text is better, the optimal selection of the text is realized, a text visualization interaction terminal is designed, and model optimization and method verification are facilitated.
Description
technical field [0001] The invention relates to an evaluation system, in particular to a deep learning-based text generation and evaluation system with emotional labels. Background technique [0002] With the rise of social networks such as Facebook and Twitter, the Internet has not only become an important source of information for people, but also a platform for people to express their opinions. By commenting on hot events, expressing film review opinions, describing product experience, etc. in blogs, topics, Twitter and other online communities, a large amount of text information with emotional tendencies is generated, and by performing sentiment analysis on these text information, we can better understand User behavior, discovering users' inclinations to products, degree of attention to hot events, etc. With the rapid increase of information scale, it is impossible to complete this task only by manual processing, which promotes a research hotspot in the field of natural...
Claims
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IPC IPC(8): G06F16/35G06K9/62G06N3/04G06N3/08
CPCG06F16/35G06N3/08G06N3/044G06N3/045G06F18/241
Inventor 任磊赵力
Owner BEIHANG UNIV
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