A study of various text augmentation techniques for relation classification in free text
Setúbal, Portugal : SciTePress Digital Library
InProceedings of the 8th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2019, Vol. 1), pp. 360-367
ICPRAM: 8th International Conference on Pattern Recognition Applications and Methods (Prague, Czech Republic, 19-21 February, 2019)
Article in monograph or in proceedings
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Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2019, Vol. 1)
Data augmentation techniques have been widely used in visual recognition tasks as it is easy to generate new data by simple and straight forward image transformations. However, when it comes to text data augmentations, it is difficult to find appropriate transformation techniques which also preserve the contextual and grammatical structure of language texts. In this paper, we explore various text data augmentation techniques in text space and word embedding space. We study the effect of various augmented datasets on the efficiency of different deep learning models for relation classification in text.
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