Solving problems two at a time: classification of web pages using a generic pair-wise multiple classifier system

Authors:
Hassan Alam;Fuad Rahman;Yuliya Tarnikova
Affiliations:
BCL Technologies Inc., Santa Clara, CA;BCL Technologies Inc., Santa Clara, CA;BCL Technologies Inc., Santa Clara, CA
Venue:
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
Year:
2003

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Abstract

We propose a generic multiple classifier system based solely on pairwise classifiers to classify web pages. Web page classification is getting huge attention now because of its use in enhancing the accuracy of search engines and in summarizing web content for small-screen handheld devices. We have used a Support Vector Machine (SVM) as our core pair-wise classifier. The proposed system has produced very encouraging results on the problem web page classification. The proposed solution is totally generic and should be applicable in solving a wide range of multiple class pattern recognition problems.