A Study of Various Text Augmentation Techniques for Relation Classification in 
Free Text

Badimala, Praveen; Mishra, Chinmaya; Venkataramana, Reddy Kumar Modam; Bukhari, Syed Saqib; Dengel, Andreas

doi:10.5220/0007311003600367

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A Study of Various Text Augmentation Techniques for Relation Classification in Free Text

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Citation

Badimala, P., Mishra, C., Venkataramana, R. K. M., Bukhari, S. S., & Dengel, A. (2019). A Study of Various Text Augmentation Techniques for Relation Classification in Free Text. In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods (pp. 360-367). Setúbal, Portugal: SciTePress Digital Library. doi:10.5220/0007311003600367.

Cite as: https://hdl.handle.net/21.11116/0000-000E-A890-1

Abstract

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 augmen-
tations, 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.