Data Augmentation Using Transformers and Similarity Measures for Improving Arabic Text Classification

Data Augmentation Using Transformers and Similarity Measures for Improving Arabic Text Classification

The performance of learning models heavily relies on the availability and adequacy of training data. To address the dataset adequacy issue, researchers have extensively explored data augmentation (DA) as a promising approach. DA generates new data instances through transformations applied to the ava...

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Bibliographic Details
Main Authors: Dania Refai, Saleh Abu-Soud, Mohammad J. Abdel-Rahman
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Arabic
AraBERT
AraGPT-2
data augmentation
machine learning
natural language processing
Online Access:https://ieeexplore.ieee.org/document/10328600/

Internet

https://ieeexplore.ieee.org/document/10328600/

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