@inproceedings{3e14a0c4c558438c94616d775b2199b2,
title = "Lexical Data Augmentation for Text Classification in Deep Learning",
abstract = "This paper presents our work on using part-of-speech focused lexical substitution for data augmentation (PLSDA) to enhance the prediction capabilities and the performance of deep learning models. This paper explains how PLSDA uses part-of-speech information to identify words and make use of different augmentation strategies to find semantically related substitutions to generate new instances for training. Evaluations of PLSDA is conducted on a variety of datasets across different text classification tasks. When PLSDA is applied to four deep learning models, results show that classifiers trained with PLSDA achieve 1.3% accuracy improvement on average.",
keywords = "Data augmentation, Deep learning, Lexical data augmentation, Text classification",
author = "Rong Xiang and Emmanuele Chersoni and Yunfei Long and Qin Lu and Huang, {Chu Ren}",
note = "Funding Information: Acknowledgements. We acknowledge the research grants from Hong Kong Polytechnic University (PolyU RTVU) and GRF grant (CERG PolyU 15211/14E, PolyU 152006/16E). Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020.; 33rd Canadian Conference on Artificial Intelligence, Canadian AI 2020 ; Conference date: 13-05-2020 Through 15-05-2020",
year = "2020",
month = jan,
day = "1",
doi = "10.1007/978-3-030-47358-7_53",
language = "English",
isbn = "9783030473570",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "521--527",
editor = "Cyril Goutte and Xiaodan Zhu",
booktitle = "Advances in Artificial Intelligence - 33rd Canadian Conference on Artificial Intelligence, Canadian AI 2020, Proceedings",
}