Comparative Analysis of Existing Deep Learning and Transformer-Based Models for Telugu News Article Classification
Keywords:
Telugu News Classification, Natural Language Processing, Deep Learning, Bidirectional Long Short-Term Memory (BiLSTM), Graph Neural Network (GNN), ULMFiT, ALBERT, Comparative Analysis.Abstract
News Article Classification in Telugu is one of thetrending topics in Natural Language processing since digital
news articles are on rise and processing low resource languagesis a challenging task. Different deep learning and transformer based architectures are proposed to improve the classificationperformance of news articles but a comprehensive
References
[1] Howard, J., and Ruder, S., “Universal Language Model Fine-Tuning for Text Classification,” Proceedings of the 56th Annual Meeting of
the Association for Computational Linguistics (ACL), Melbourne, Australia, pp. 328–339, 2018.
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Published
2024-12-20
How to Cite
V. Premalatha , Dr. P. Dileep Kumar Reddy. (2024). Comparative Analysis of Existing Deep Learning and Transformer-Based Models for Telugu News Article Classification. Journal of Computational Analysis and Applications (JoCAAA), 33(08), 7838–7847. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/5845
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