Mohammed, Athraa Jasim and Yusof, Yuhanis and Husni, Husniza (2014) Experimental analysis of firefly algorithms for divisive clustering of web documents. Recent Advances on Soft Computing and Data Mining, 287. pp. 487-496. ISSN 2194-5357

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Abstract

This paper studies two clustering algorithms that are based on the Firefly Algorithm (FA) which is a recent swarm intelligence approach.We perform experiments utilizing the Newton’s Universal Gravitation Inspired Firefly Algorithm (GFA) and Weight-Based Firefly Algorithm (WFA) on the 20_newsgroups dataset.The analysis is undertaken on two parameters.The first is the alpha (α) value in the Firefly algorithms and latter is the threshold value required during clustering process. Results showed that a better performance is demonstrated by Weight-Based Firefly Algorithm compared to Newton’s Universal Gravitation Inspired Firefly Algorithm.

Item Type:	Article
Additional Information:	Proceedings of The First International Conference on Soft Computing and Data Mining (SCDM-2014) Universiti Tun Hussein Onn Malaysia, Johor, MalaysiaJune 16th-18th, 2014
Uncontrolled Keywords:	Firefly algorithm text clustering divisive clustering
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Divisions:	School of Computing
Depositing User:	Dr. Yuhanis Yusof
Date Deposited:	09 Sep 2015 09:23
Last Modified:	22 May 2016 07:46
URI:	https://repo.uum.edu.my/id/eprint/15450

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