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Extended VSM for XML Document Classification Using Frequent Subtrees

  • Conference paper
Focused Retrieval and Evaluation (INEX 2009)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6203))

Abstract

Structured link vector model (SLVM) is a representation proposed for modeling XML documents, which was extended from the conventional vector space model (VSM) by incorporating document structures. In this paper, we describe the classification approach for XML documents based on SLVM in the Document Mining Challenge of INEX 2009, where the closed frequent subtrees as structural units are used for content extraction from the XML document and the Chi-square test is used for feature selection.

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Author information

Authors and Affiliations

  1. Institute of Computer Sci. & Tech., Peking University, Beijing, 100871, China

    Jianwu Yang & Songlin Wang

Authors
  1. Jianwu Yang
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  2. Songlin Wang
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Editor information

Editors and Affiliations

  1. Faculty of Science and Technology, Queensland University of Technology, GPO Box 2434, 4001, Brisbane, Qld, Australia

    Shlomo Geva

  2. Archives and Information Studies/Humanities, University of Amsterdam, Turfdraagsterpad 9, 1012 XT, Amsterdam, The Netherlands

    Jaap Kamps

  3. Department of Computer Science, University of Otago, P.O. Box 56,, 9054, Dunedin, New Zealand

    Andrew Trotman

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Yang, J., Wang, S. (2010). Extended VSM for XML Document Classification Using Frequent Subtrees. In: Geva, S., Kamps, J., Trotman, A. (eds) Focused Retrieval and Evaluation. INEX 2009. Lecture Notes in Computer Science, vol 6203. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14556-8_44

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  • DOI: https://doi.org/10.1007/978-3-642-14556-8_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14555-1

  • Online ISBN: 978-3-642-14556-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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