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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Bibliographic Details
Published in:International journal of machine learning and cybernetics Vol. 14; no. 1; pp. 135 - 150
Main Authors: Bayer, Markus, Kaufhold, Marc-André, Buchhold, Björn, Keller, Marcel, Dallmeyer, Jörg, Reuter, Christian
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2023
Springer Nature B.V
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ISSN:1868-8071, 1868-808X, 1868-808X
Online Access:Get full text
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