Survey on Particle Swarm Optimization Based Web Mining
نویسنده
چکیده
Web Mining is a challenging task that searches for Web access patterns, Web structures and the regularity and dynamics of the Web contents. It provides efficient Web Personalization, System Improvement, Site Modification, Business Intelligence and Usage Characterization. High-dimensional Web Log File clustering is a challenging task and requires an efficient clustering technique. The efficiency and simplicity of Particle Swarm Optimization has been exploited for this challenging task and has proved to be a better choice for web session clustering, user profile clustering, page clustering and for many other applications of Web Mining as compared to the traditional K-means clustering method. This paper provides an extensive survey of the application of PSO technique and its variants to Web Usage Mining. Section I of this paper gives a basic introduction to Web Mining, Web Usage Mining and PSO. Section II explains in brief the PSO Clustering technique. Section III discusses in detail the various PSO based techniques used for Web Usage Mining and Section IV concludes the significance of PSO in Web Usage Mining.
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