Hijazi, Musab and Zeki, Akram M. and Ismail, Amelia Ritahani (2023) Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification. The International Arab Journal of Information Technology, 20 (3A (Special Issue)). pp. 536-547. ISSN 1683-3198 E-ISSN 2309-4524
|
PDF (SCOPUS)
- Supplemental Material
Download (212kB) | Preview |
|
PDF (Article)
- Published Version
Restricted to Registered users only Download (746kB) | Request a copy |
Abstract
A huge amount of crucial information is contained in documents. The vast increase in the number of E documents available for user access makes the utilization of automated text classification es sential. Classifying or arranging documents into predefined group s is called Text classification Feature Selection (is needed for minimizing the dimensionality of high dimensional data and extracting only the features that are most pertinent to a particular task. One of the widely used algorithms for feature selection in text classification is the Evolutionary algorithm . In this paper, the filter method chi square and the Artificial Bee Colony) ABC algorithm were both used as FS methods . The chi square method is a useful technique for reducing the number of features and removing those that are superfluous or redundant. The ABC technique considers the chi square methods' chosen features as viable solutions (food sources). The ABC algorithm searches for the most efficient selection of features that increase classification performance. Support Vector Machine and Naïve Bayes classifiers were used as a fitness function for the ABC algorithm. The experiment result s demonstrated that the proposed feature selection method was able of decreasing the number of features by approximately 89.5%, and 94%, respectively when NB and SVM were used as fitness functions in comparison to the original dataset, while also enhancing classification performance.
Item Type: | Article (Journal) |
---|---|
Uncontrolled Keywords: | Artificial bee colony, Arabic text classification, wrapper feature selection, feature selection, |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering |
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System |
Depositing User: | Akram M Zeki |
Date Deposited: | 01 Feb 2024 09:22 |
Last Modified: | 01 Feb 2024 09:24 |
URI: | http://irep.iium.edu.my/id/eprint/110656 |
Actions (login required)
View Item |