Text Classification with the Whale Swarm Algorithm: A New Perspective
Marzouk, O., F. Shawish, A., Fathi, H., S. Othman, E. (2023). Text Classification with the Whale Swarm Algorithm: A New Perspective. EKB Journal Management System, 2(1), 1-10. doi: 10.21608/jcsit.2023.238411.1000
Osama Marzouk; Amr F. F. Shawish; Hanaa Fathi; Emad S. Othman. "Text Classification with the Whale Swarm Algorithm: A New Perspective". EKB Journal Management System, 2, 1, 2023, 1-10. doi: 10.21608/jcsit.2023.238411.1000
Marzouk, O., F. Shawish, A., Fathi, H., S. Othman, E. (2023). 'Text Classification with the Whale Swarm Algorithm: A New Perspective', EKB Journal Management System, 2(1), pp. 1-10. doi: 10.21608/jcsit.2023.238411.1000
Marzouk, O., F. Shawish, A., Fathi, H., S. Othman, E. Text Classification with the Whale Swarm Algorithm: A New Perspective. EKB Journal Management System, 2023; 2(1): 1-10. doi: 10.21608/jcsit.2023.238411.1000

Text Classification with the Whale Swarm Algorithm: A New Perspective

Journal of Communication Sciences and Information Technology
Volume 2, Issue 1, October 2023, Page 1-10  XML PDF (434.16 K)
Document Type: Original Article
DOI: 10.21608/jcsit.2023.238411.1000
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Authors
Osama Marzouk email orcid ; Amr F. F. Shawish1; Hanaa Fathi2; Emad S. Othman3
1Lecture computer science in October Higher Institute of Engineering and Technology in 6 October city, Egypt.
2Mathematics & Computer Science Department, Faculty of Science Menofia University.
3Country Assoc. Professor of computer and Information Systems, EL-Shorouk Academy, Cairo – Egypt.
Abstract
The increasing popularity of nature-inspired meta-heuristic algorithms in real-world optimization problems has been attributed to their advantages over traditional numerical optimization techniques. This study introduces the Whale Swarm Algorithm (WSA), a nature-inspired meta-heuristic, which draws inspiration from whales' communication through ultrasound for hunting. The focus of this paper is on using WSA for feature optimization. Text mining finds applications in various domains, such as business intelligence, social media analysis, sentiment analysis, biomedical analysis, software process analysis, and security analysis. This paper explores the use of WSA as an optimization algorithm, particularly in automating the understanding of Arabic text and constructing ontologies. Additionally, the paper delves into the challenges faced in enhancing the WSA models. Furthermore, this research presents a comprehensive overview of the diverse applications of WSA in different fields, with a specific emphasis on its role in ontology learning from Arabic text, aiming to improve swarm optimization techniques in practical use cases.
Keywords
optimization; swarm intelligence; whal
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