Data Scarcity: Methods to Improve the Quality of Text Classification

Ingo Glaser, Shabnam Sadegharmaki, Basil Komboz, Florian Matthes

2021

Abstract

Legal document analysis is an important research area. The classification of clauses or sentences enables valuable insights such as the extraction of rights and obligations. However, datasets consisting of contracts or other legal documents are quite rare, particularly regarding the German language. The exorbitant cost of manually labeled data, especially in regard to text classification, is the motivation of many studies that suggest alternative methods to overcome the lack of labeled data. This paper experiments the effects of text data augmentation on the quality of classification tasks. While a large amount of techniques exists, this work examines a selected subset including semi-supervised learning methods and thesaurus-based data augmentation. We could not just show that thesaurus-based data augmentation as well as text augmentation with synonyms and hypernyms can improve the classification results, but also that the effect of such methods depends on the underlying data structure.

Paper Citation

in Harvard Style

Glaser I., Sadegharmaki S., Komboz B. and Matthes F. (2021). Data Scarcity: Methods to Improve the Quality of Text Classification.In Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-486-2, pages 556-564. DOI: 10.5220/0010268005560564

in Bibtex Style

@conference{icpram21,
author={Ingo Glaser and Shabnam Sadegharmaki and Basil Komboz and Florian Matthes},
title={Data Scarcity: Methods to Improve the Quality of Text Classification},
booktitle={Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2021},
pages={556-564},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010268005560564},
isbn={978-989-758-486-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Data Scarcity: Methods to Improve the Quality of Text Classification
SN - 978-989-758-486-2
AU - Glaser I.
AU - Sadegharmaki S.
AU - Komboz B.
AU - Matthes F.
PY - 2021
SP - 556
EP - 564
DO - 10.5220/0010268005560564