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Solving Problems Two at a Time: Classification of Web Pages Using a Generic Pair-Wise Multiple Classifier System

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Multiple Classifier Systems (MCS 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2709))

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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.

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Author information

Authors and Affiliations

  1. BCL Technologies Inc., 990 Linden Dr., Suite #203, Santa Clara, CA, 95050, USA

    Hassan Alam, Fuad Rahman, Fuad Rahman & Yuliya Tarnikova

Authors
  1. Hassan Alam
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  2. Fuad Rahman
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  3. Yuliya Tarnikova
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Editor information

Editors and Affiliations

  1. Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, Surrey, GU2 7XH, UK

    Terry Windeatt

  2. Dept. of Electrical and Electronic Engineering, University of Cagliari, Piazza D’Ami, 09123, Cagliari, Italy

    Fabio Roli

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© 2003 Springer-Verlag Berlin Heidelberg

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Alam, H., Rahman, F., Tarnikova, Y. (2003). Solving Problems Two at a Time: Classification of Web Pages Using a Generic Pair-Wise Multiple Classifier System. In: Windeatt, T., Roli, F. (eds) Multiple Classifier Systems. MCS 2003. Lecture Notes in Computer Science, vol 2709. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44938-8_39

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  • DOI: https://doi.org/10.1007/3-540-44938-8_39

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40369-2

  • Online ISBN: 978-3-540-44938-6

  • eBook Packages: Springer Book Archive

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