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Comparative analysis of deep learning approaches for scientific literature classification

Authors: Ahanger, M.M. and Wani, M.A.

Journal: Proceedings of the 2021 8th International Conference on Computing for Sustainable Global Development, INDIACom 2021

Pages: 74-80

ISBN: 9789380544434

DOI: 10.1109/INDIACom51348.2021.00015

Abstract:

Automatic document categorization has emerged as a significant application of supervised learning. Deep learning has among other fields is revolutionizing document categorization. Recently, deep learning has been applied to classify scientific literature. This paper presents a comparative analysis of various deep learning-based text classification approaches for scientific literature classification. The purpose of this study is to explore the applicability of such algorithms on the task of classifying scientific literature. We describe and apply deep learning-based text classification algorithms on various datasets. The experimental results show that deep learning-based text classification algorithms are applicable and perform well on the task.

Source: Scopus