Experimental Analysis of Firefly Algorithms for Divisive Clustering of Web Documents

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.

[1]  Janez Brest,et al.  A comprehensive review of firefly algorithms , 2013, Swarm Evol. Comput..

[2]  Mohammad S. Obaidat,et al.  Advances in Computer Science and its Applications (CSA 2013) , 2013 .

[3]  Tamalika Chaira,et al.  A novel intuitionistic fuzzy C means clustering algorithm and its application to medical images , 2011, Appl. Soft Comput..

[4]  Taufik Abrão,et al.  Anomaly Detection Using Metaheuristic Firefly Harmonic Clustering , 2013, J. Networks.

[5]  Moe Moe Zaw,et al.  Web Document Clustering Using Cuckoo Search Clustering Algorithm based on Levy Flight , 2013 .

[6]  Franz Rothlauf,et al.  Design of Modern Heuristics , 2011, Natural Computing Series.

[7]  K. Faez,et al.  A speech recognition system based on Structure Equivalent Fuzzy Neural Network trained by Firefly algorithm , 2012, 2012 International Conference on Biomedical Engineering (ICoBE).

[8]  OzturkCelal,et al.  A novel clustering approach , 2011 .

[9]  Jemal H. Abawajy,et al.  Proceedings of the First International Conference on Advanced Data and Information Engineering, DaEng 2013, Kuala Lumpur, Malaysia, December 16-18, 2013 , 2014, DaEng.

[10]  K. Murugesan,et al.  Hybrid Bisect K-Means Clustering Algorithm , 2011, 2011 International Conference on Business Computing and Global Informatization.

[11]  Hema Banati,et al.  Performance analysis of firefly algorithm for data clustering , 2013 .

[12]  Ming-Huwi Horng,et al.  Multilevel Image Thresholding Selection Based on the Firefly Algorithm , 2010, 2010 7th International Conference on Ubiquitous Intelligence & Computing and 7th International Conference on Autonomic & Trusted Computing.

[13]  Mohammad Reza Meybodi,et al.  A new hybrid approach for data clustering using firefly algorithm and K-means , 2012, The 16th CSI International Symposium on Artificial Intelligence and Signal Processing (AISP 2012).

[14]  Xin-She Yang,et al.  Firefly Algorithm: Recent Advances and Applications , 2013, ArXiv.

[15]  Dervis Karaboga,et al.  A novel clustering approach: Artificial Bee Colony (ABC) algorithm , 2011, Appl. Soft Comput..

[16]  Xin-She Yang,et al.  Nature-Inspired Metaheuristic Algorithms , 2008 .

[17]  Jacek M. Zurada,et al.  Swarm and Evolutionary Computation , 2012, Lecture Notes in Computer Science.

[18]  Tie-Yan Liu,et al.  Information Retrieval Technology , 2014, Lecture Notes in Computer Science.

[19]  Mohamed S. Kamel,et al.  Enhanced bisecting k-means clustering using intermediate cooperation , 2009, Pattern Recognit..

[20]  Li Xiu,et al.  Application of data mining techniques in customer relationship management: A literature review and classification , 2009, Expert Syst. Appl..

[21]  Kai Liu,et al.  A fast divisive clustering algorithm using an improved discrete particle swarm optimizer , 2010, Pattern Recognit. Lett..

[22]  Dongsong Zhang,et al.  Discovering golden nuggets: data mining in financial application , 2004, IEEE Trans. Syst. Man Cybern. Part C.

[23]  Mario Kusek,et al.  A self-optimizing mobile network: Auto-tuning the network with firefly-synchronized agents , 2012, Inf. Sci..

[24]  Soon Myoung Chung,et al.  Text document clustering based on neighbors , 2009, Data Knowl. Eng..

[25]  Michael Wolfe,et al.  J+ = J , 1994, ACM SIGPLAN Notices.

[26]  Mohammad Kazem Sayadi,et al.  Firefly-inspired algorithm for discrete optimization problems: An application to manufacturing cell formation , 2013 .

[27]  Franz Rothlauf,et al.  Design of Modern Heuristics: Principles and Application , 2011 .

[28]  Husniza Husni,et al.  Weight-Based Firefly Algorithm for Document Clustering , 2013, DaEng.

[29]  Husniza Husni,et al.  A Newton’s Universal Gravitation Inspired Firefly Algorithm for Document Clustering , 2014 .

[30]  Anil K. Jain.  Data clustering: 50 years beyond K-means , 2010, Pattern Recognit. Lett..

[31]  Siu Cheung Hui,et al.  A Novel Ant-Based Clustering Approach for Document Clustering , 2006, AIRS.

[32]  V. Mani,et al.  Clustering using firefly algorithm: Performance study , 2011, Swarm Evol. Comput..

[33]  Amir Hossein Gandomi,et al.  Firefly Algorithm for solving non-convex economic dispatch problems with valve loading effect , 2012, Appl. Soft Comput..