Text Classification Using Deep Learning Models: A Comparative Review

Authors

  • Muhammad Zulqarnain Faculty of Computing, The Islamia University of Bahawalpur, Punjab, Pakistan
  • Rubab Sheikh Faculty of Computing, The Islamia University of Bahawalpur, Punjab, Pakistan
  • Shahid Hussain Faculty of Computing, The Islamia University of Bahawalpur, Punjab, Pakistan
  • Muhammad Sajid Faculty of Computing, The Islamia University of Bahawalpur, Punjab, Pakistan
  • Syed Naseem Abbas Faculty of Computing, The Islamia University of Bahawalpur, Punjab, Pakistan
  • Muhammad Majid Faculty of Computing, The Islamia University of Bahawalpur, Punjab, Pakistan
  • Ubaid Ullah College of Computing, Riphah International University, Faisalabad Campus, Pakistan

DOI:

https://doi.org/10.37256/ccds.5120243528

Keywords:

deep learning, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Deep Belief Networks (DBN), text classification

Abstract

With the fast popularization and continued development of web pages on the Internet, text classification has become a very serious problem in organizing and managing large amounts of digital text data in documents. The deep learning approaches have been applied in several areas of text classification with comparative and outstanding results. In this article, we analyzed and gave comprehensive reviews of the different deep learning models for text classification tasks. Based on the literature review survey, this paper addresses three various deep learning models and declares their gaps and limitations. We have evaluated the various classification applications and a small discussion on the available Deep Neural Networks (DNN) frameworks for the implementation of text datasets. The work presents guidance for future research to regulate more significance that can be distributed for the better area of this research. In summary, our study presented the main implications, identified potential directions for future research, and highlighted the challenges within this specific research field. Additionally, our aim is to acquaint readers with the various subtasks and relevant literature related to the text classification process. By engaging with our discussion, we aspire to inspire readers to explore novel and enhanced techniques for text classification, applicable across diverse domains.

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Published

2023-10-16

How to Cite

1.
Muhammad Zulqarnain, Rubab Sheikh, Shahid Hussain, Muhammad Sajid, Syed Naseem Abbas, Muhammad Majid, Ubaid Ullah. Text Classification Using Deep Learning Models: A Comparative Review. Cloud Computing and Data Science [Internet]. 2023 Oct. 16 [cited 2024 Dec. 5];5(1):80-96. Available from: https://ojs.wiserpub.com/index.php/CCDS/article/view/3528