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

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.

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Giridhara et al_2019_study_of_various_text.pdf (Publisher version), 351KB
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Giridhara et al_2019_study_of_various_text.pdf
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2019
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 Creators:
Badimala, Praveen1, 2, Author
Mishra, Chinmaya1, 2, Author           
Venkataramana, Reddy Kumar Modam1, Author
Bukhari, Syed Saqib2, Author
Dengel, Andreas2, Author
Affiliations:
1Department of Computer Science, TU Kaiserslautern, Kaiserslautern, Germany, ou_persistent22              
2German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany, ou_persistent22              

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 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.

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Language(s): eng - English
 Dates: 2019
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.5220/0007311003600367
 Degree: -

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Title: 8th International Conference on Pattern Recognition Applications and Methods
Place of Event: Prague, Czech republic
Start-/End Date: 2019-02-19 - 2019-02-21

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Title: Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods
Source Genre: Proceedings
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Publ. Info: Setúbal, Portugal : SciTePress Digital Library
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 360 - 367 Identifier: -