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Authors: Praveen Giridhara 1 ; Chinmaya Mishra 1 ; Reddy Venkataramana 2 ; Syed Bukhari 3 and Andreas Dengel 1

Affiliations: 1 Department of Computer Science, TU Kaiserslautern, Gottlieb-Daimler-Straße 47, Kaiserslautern, Germany, German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany ; 2 Department of Computer Science, TU Kaiserslautern, Gottlieb-Daimler-Straße 47, Kaiserslautern, Germany ; 3 German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany

ISBN: 978-989-758-351-3

Keyword(s): Relation Classification, Text Data Augmentation, Natural Language Processing, Investigative Study.

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 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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Paper citation in several formats:
Giridhara, P.; Mishra, C.; Venkataramana, R.; Bukhari, S. and 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 - Volume 1: ICPRAM, ISBN 978-989-758-351-3, pages 360-367. DOI: 10.5220/0007311003600367

@conference{icpram19,
author={Praveen Kumar Badimala Giridhara. and Chinmaya Mishra. and Reddy Kumar Modam Venkataramana. and Syed Saqib Bukhari. and Andreas Dengel.},
title={A Study of Various Text Augmentation Techniques for Relation Classification in Free Text},
booktitle={Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2019},
pages={360-367},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007311003600367},
isbn={978-989-758-351-3},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - A Study of Various Text Augmentation Techniques for Relation Classification in Free Text
SN - 978-989-758-351-3
AU - Giridhara, P.
AU - Mishra, C.
AU - Venkataramana, R.
AU - Bukhari, S.
AU - Dengel, A.
PY - 2019
SP - 360
EP - 367
DO - 10.5220/0007311003600367

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