Data augmentation in natural language processing: a novel text generation approach for long and short text classifiers
In many cases of machine learning, research suggests that the development of training data might have a higher relevance than the choice and modelling of classifiers themselves. Thus, data augmentation methods have been developed to improve classifiers by artificially created training data. In NLP,...
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| Published in: | International journal of machine learning and cybernetics Vol. 14; no. 1; pp. 135 - 150 |
|---|---|
| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.01.2023
Springer Nature B.V |
| Subjects: | |
| ISSN: | 1868-8071, 1868-808X, 1868-808X |
| Online Access: | Get full text |
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