Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/8816
Title: Learning web categorization with controlled generation of context features
Authors: Wong, AKS
Lee, JWT
Yeung, DS
Keywords: Internet
Classification
Learning (artificial intelligence)
Text analysis
Issue Date: 2006
Publisher: IEEE
Source: IEEE International Conference on Systems, Man and Cybernetics, 2006 : SMC '06, 8-11 October 2006, Taipei, p. 2960-2964 How to cite?
Abstract: Automatic categorization of Web pages is an important area of study due to the rapidly growing amount of Web data. Efficient and accurate classification would greatly facilitate finding what one needs in the sea of information. Context-sensitive techniques have been proven to be effective in the classification task. However, the feature space for context feature that one can explore in these techniques is enormous. To consider these features comprehensively often become prohibitive in terms of resource requirements. In this paper, we propose an approach to intelligently control generating context features for the classification learning process. We present our investigation of this approach in the context of Web page categorization using the sleeping-experts technique.
URI: http://hdl.handle.net/10397/8816
ISBN: 1-4244-0099-6
1-4244-0100-3 (E-ISBN)
DOI: 10.1109/ICSMC.2006.384568
Appears in Collections:Conference Paper

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