Feature selection with rough sets for web page classification

Authors:
Aijun An;Yanhui Huang;Xiangji Huang;Nick Cercone
Affiliations:
York University, Toronto, Ontario, Canada;University of Waterloo, Waterloo, Ontario, Canada;University of Waterloo, Waterloo, Ontario, Canada;Dalhousie University, Halifax, Nova Scotia, Canada
Venue:
Transactions on Rough Sets II
Year:
2005

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Abstract

Web page classification is the problem of assigning predefined categories to web pages. A challenge in web page classification is how to deal with the high dimensionality of the feature space. We present a feature reduction method based on the rough set theory and investigate the effectiveness of the rough set feature selection method on web page classification. Our experiments indicate that rough set feature selection can improve the predictive performance when the original feature set for representing web pages is large.