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Mining Usage Web Log Via Independent Component Analysis And Rough Fuzzy

Siriporn, Chimphlee and Salim, Naomie and Ngadiman , Mohd Salihin and Witcha, Chimphlee and Surat, Srinoy (2006) Mining Usage Web Log Via Independent Component Analysis And Rough Fuzzy. In: procedings of the 5th WSEAS International Conference on, 15-17 february 2006, Masrid, Spain..

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Abstract

In the past few years, web usage mining techniques have grown rapidly together with the explosive growth of the web, both in the research and commercial areas. Web Usage Mining is that area of Web Mining which deals with the extraction of interesting knowledge from logging information produced by Web servers. A challenge in web classification is how to deal with the high dimensionality of the feature space. In this paper we present Independent Component Analysis (ICA) for feature selection and using Rough Fuzzy for clustering web user sessions. Our experiments indicate can improve the predictive performance when the original feature set for representing web log is large and can handling the different groups of uncertainties/impreciseness accuracy.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Web Usage Mining; Web log mining;Independent component analysis; Rough Sets; Fuzzy rough sets;
Subjects:Q Science > QA Mathematics > QA76 Computer software
Divisions:Computer Science and Information System (Formerly known)
ID Code:3181
Deposited By: Norazlizafarah Anuar
Deposited On:24 May 2007 07:23
Last Modified:01 Jun 2010 03:07

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