<b>Text Classification with Deep Learning and Transfer Learning: A Survey</b>

This paper review 2 Section briefly discusses the evolution of the text classification algorithms including rule-based and traditional machine learning approaches and deep learning models including pre-trained models. Being one of the significant areas in the NLP [1] text classification is useful for many uses including search and analysis of opinions within texts. The AI tools like ImageAI CNN, RNN and pre-trained models like BERT [2] In performing classification on text is emphasized and how each play a vital role in dealing with large and complex texts accordingly. The problem and directions for future work for the text classifications are also outlined advice to researchers and some practitioners in the study area.

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Publication Details

Journal
Annual Methodological Archive Research Review
Published
2025-07-13
DOI
https://doi.org/10.63075/mvp6rq97
Primary Topic
Text and Document Classification Technologies
Type
article
Field-Weighted Citation Impact
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article

Text Classification with Deep Learning and Transfer Learning: A Survey

Talha Farooq Khan, Reiaz Ul Rehman, Mubasher Malik, Muhammad Sabir
Annual Methodological Archive Research Review
Text and Document Classification Technologies
article

Text Classification with Deep Learning and Transfer Learning: A Survey

Talha Farooq Khan, Reiaz Ul Rehman, Mubasher Malik, Muhammad Sabir
article en

Abstract

This paper review 2 Section briefly discusses the evolution of the text classification algorithms including rule-based and traditional machine learning approaches and deep learning models including pre-trained models. Being one of the significant areas in the NLP [1] text classification is useful for many uses including search and analysis of opinions within texts. The AI tools like ImageAI CNN, RNN and pre-trained models like BERT [2] In performing classification on text is emphasized and how each play a vital role in dealing with large and complex texts accordingly. The problem and directions for future work for the text classifications are also outlined advice to researchers and some practitioners in the study area.

Annual Methodological Archive Research ReviewVol. 3(7)
Muhammad Nawaz Shareef University of Agriculture (PK)
Openalex Percentile: Top 92%
Text and Document Classification Technologies
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