The week's pick
Reseach Article
Binary Particle Swarm Optimization based Biclustering of Web usage Data
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 25 - Number 2 |
| Year of Publication: 2011 |
| Authors: R.Rathipriya, K.Thangavel, J.Bagyamani |
10.5120/3001-4036
|
R.Rathipriya, K.Thangavel, J.Bagyamani . Binary Particle Swarm Optimization based Biclustering of Web usage Data. International Journal of Computer Applications. 25, 2 ( July 2011), 43-49. DOI=10.5120/3001-4036
Abstract
Web mining is the nontrivial process to discover valid, novel, potentially useful knowledge from web data using the data mining techniques or methods. It may give information that is useful for improving the services offered by web portals and information access and retrieval tools. With the rapid development of biclustering, more researchers have applied the biclustering technique to different fields in recent years. When biclustering approach is applied to the web usage data it automatically captures the hidden browsing patterns from it in the form of biclusters. In this work, swarm intelligent technique is combined with biclustering approach to propose an algorithm called Binary Particle Swarm Optimization (BPSO) based Biclustering for Web Usage Data. The main objective of this algorithm is to retrieve the global optimal bicluster from the web usage data. These biclusters contain relationships between web users and web pages which are useful for the E-Commerce applications like web advertising and marketing. Experiments are conducted on real dataset to prove the efficiency of the proposed algorithms.
References
- Srivastava. J, Cooley. R, Deshpande, and P.-N. Tan, “Web usage mining: Discovery and applications of usage patterns from web data,” SIGKDD Explorations, vol. 1, no. 2, pp. 12-23, 2000.
- Sandro Araya, Mariano Silva, Richard Weber, A methodology for web usage mining and its application to target group identification, Fuzzy Sets and Systems, pp:139–152,2004.
- Xu, R. and Wunsch, D.I. ,‘Survey of clustering algorithms’, IEEE Transactions on Neural Networks, Vol. 16, No. 3, pp.645–678, 2005.
- Madeira and Oliveira, “Biclustering algorithms for biological data analysis: a survey”, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2004.
- Koutsonikola, V.A. and Vakali, A. , “A fuzzy bi-clustering approach to correlate web users and pages”, Int. J. Knowledge and Web Intelligence, vol. 1, no. 1/2, pp.3–23, 2009.
- Tang C and Zhang A, Interrelated Two-Way Clustering: An Unsupervised Approach for Gene Expression Data Analysis, Proc. Second IEEE Int'l Symp. Bioinformatics and Bioeng., Vol. 14, pp:41-48, 2001.
- 7. Liu, X., He, P. and Yang, Q.,Mining user access patterns based on Web logs‘, Canadian Conference on Electrical and Computer Engineering, pp.2280–2283, 2005.
- Banka H. and Mitra S., “Multi-objective Evolutionary biclustering of gene expression data”, Journal of Pattern Recognition, vol.39, pp. 2464-2477, 2006.
- Bleuler, S., Prelic, A., Zitzler, E.: An EA framework for biclustering of gene expression data. In: Congress on Evolutionary Computation CEC2004,vol.1, pp. 166–173,2004.
- Aboul-Ella Hassanien, Mariofanna G. Milanova, Tomasz G. Smolinski, Ajith Abraham, Computational Intelligence in Solving Bioinformatics Problems: Reviews,Perspectives, and Challenges,zomp. Intel. in Biomed. & Bioinform., SCI,vol. 151, pp. 3–47, 2008.
- A. Abraham, He Guo, and Hongbo Liu, Swarm Intelligence: Foundations, Perspectives and Applications, Studies in Computational Intelligence (SCI),vol. 26, pp.3–25,2006.
- A. Khosla , Shakti Kumar, K.K. Aggarwal, and Jagatpreet Singh, A Matlab Implementation of Swarm Intelligence based Methodology for Identification of Optimized Fuzzy Models, Studies in Computational Intelligence (SCI) ,vol.26, pp.175–184 ,2006.
- Anupam Chakraborty and Hitashyam Maka “Biclustering of Gene Expression Data Using Genetic Algorithm” Proceedings of Computation Intelligence in Bioinformatics and Computational Biology CIBCB, pp 1-8, 2005.
- Federico Divina and Jesus S. Aguilar-Ruize, “Biclustering of Expression Data with Evolutionary computation”, IEEE Transactions on Knowledge and Data Engineering, vol.18, pp. 590-602,2006.
- Kennedy, J. and Eberhart, R.C., A discrete binary version of the particle swarm algorithm, Systems, Man, and Cybernetics, 1997. 'Computational Cybernetics and Simulation,IEEE International Conference ,vol.5,pp. :4104 - 4108 ,1997.
- Shyama Das and Sumam Mary Idicula,” Greedy Search-Binary PSO Hybrid for Biclustering Gene Expression Data. International Journal of Computer Applications ,vol.2,no.3 , pp.1–5, 2010.
- Wu-Chang Wu and Men-Shen Tsai, Feeder Reconfiguration Using Binary Coding Particle Swarm Optimization, International Journal of Control, Automation, and Systems, vol. 6, no. 4, pp. 488-494, August 2008.
- Smitha Dharan, Achuthsankar S. Nair, "Biclustering of Gene expression Data using Reactive Greedy Randomized Adaptive Search Procedure", BMC Bioinformatics, vol. 10,2009.
Index Terms
Keywords