Empowering Multiclass Classification and Data Augmentation of Arabic News Articles Through Transformer Model-Reference-Cited by-同舟云学术

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Empowering Multiclass Classification and Data Augmentation of Arabic News Articles Through Transformer Model

Published:2024-06-30 Issue: Volume:101 Page:1-7
ISSN:
Container-title:2024 International Joint Conference on Neural Networks (IJCNN)
language:
Short-container-title:

Author:

Setu Jahanggir Hossain¹,Halder Nabarun¹,Sikder Sankar²,Islam Ashraful³,Alam Md Zahangir⁴

Affiliation:

1. Independent University Bangladesh,Department of CSE,Dhaka,Bangladesh

2. University of Louisiana at Lafayette,Department of Mathematics,Louisiana,USA

3. Independent University Bangladesh,Center for Computational & Data Sciences (CCDS),Department of CSE,Dhaka,Bangladesh

4. Independent University Bangladesh,CCDS,Department of CSE,Dhaka,Bangladesh

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10649807/10649898/10650716.pdf?arnumber=10650716

Reference22 articles.

1. A Survey on Text Classification: From Traditional to Deep Learning

2. Large scale legal text classification using transformer models;Shaheen,2020

3. Arabert: Transformer-based model for arabic language understanding;Antoun,2020

4. Systematic review of the arabic natural language processing: Challenges, techniques and new trends;Bourahouat;Journal of Theoretical and Applied Information Technology,2023

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