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Volume 10
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Article

Advances in Meta-Heuristic Optimization Algorithms in Big Data Text Clustering

by
Laith Abualigah
1,
Amir H. Gandomi
2,*,
Mohamed Abd Elaziz
3,
Husam Al Hamad
1,
Mahmoud Omari
1,
Mohammad Alshinwan
1 and
Ahmad M. Khasawneh
1
1
Faculty of Computer Sciences and Informatics, Amman Arab University, Amman 11953, Jordan
2
Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW 2007, Australia
3
Department of Mathematics, Faculty of Science, Zagazig University, Zagazig 44519, Egypt
*
Author to whom correspondence should be addressed.
Electronics 2021, 10(2), 101; https://doi.org/10.3390/electronics10020101
Submission received: 29 November 2020 / Revised: 15 December 2020 / Accepted: 22 December 2020 / Published: 6 January 2021
(This article belongs to the Special Issue Machine Learning Technologies for Big Data Analytics)
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Abstract

This paper presents a comprehensive survey of the meta-heuristic optimization algorithms on the text clustering applications and highlights its main procedures. These Artificial Intelligence (AI) algorithms are recognized as promising swarm intelligence methods due to their successful ability to solve machine learning problems, especially text clustering problems. This paper reviews all of the relevant literature on meta-heuristic-based text clustering applications, including many variants, such as basic, modified, hybridized, and multi-objective methods. As well, the main procedures of text clustering and critical discussions are given. Hence, this review reports its advantages and disadvantages and recommends potential future research paths. The main keywords that have been considered in this paper are text, clustering, meta-heuristic, optimization, and algorithm.
Keywords: meta-heuristic; optimization algorithms; machine learning; optimization problems; big data; text clustering applications meta-heuristic; optimization algorithms; machine learning; optimization problems; big data; text clustering applications

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MDPI and ACS Style

Abualigah, L.; Gandomi, A.H.; Elaziz, M.A.; Hamad, H.A.; Omari, M.; Alshinwan, M.; Khasawneh, A.M. Advances in Meta-Heuristic Optimization Algorithms in Big Data Text Clustering. Electronics 2021, 10, 101. https://doi.org/10.3390/electronics10020101

AMA Style

Abualigah L, Gandomi AH, Elaziz MA, Hamad HA, Omari M, Alshinwan M, Khasawneh AM. Advances in Meta-Heuristic Optimization Algorithms in Big Data Text Clustering. Electronics. 2021; 10(2):101. https://doi.org/10.3390/electronics10020101

Chicago/Turabian Style

Abualigah, Laith, Amir H. Gandomi, Mohamed Abd Elaziz, Husam Al Hamad, Mahmoud Omari, Mohammad Alshinwan, and Ahmad M. Khasawneh. 2021. "Advances in Meta-Heuristic Optimization Algorithms in Big Data Text Clustering" Electronics 10, no. 2: 101. https://doi.org/10.3390/electronics10020101

APA Style

Abualigah, L., Gandomi, A. H., Elaziz, M. A., Hamad, H. A., Omari, M., Alshinwan, M., & Khasawneh, A. M. (2021). Advances in Meta-Heuristic Optimization Algorithms in Big Data Text Clustering. Electronics, 10(2), 101. https://doi.org/10.3390/electronics10020101

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