Document Clustering with K-tree

  • Christopher M. De Vries
  • Shlomo Geva
Conference paper

DOI: 10.1007/978-3-642-03761-0_43

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5631)
Cite this paper as:
De Vries C.M., Geva S. (2009) Document Clustering with K-tree. In: Geva S., Kamps J., Trotman A. (eds) Advances in Focused Retrieval. INEX 2008. Lecture Notes in Computer Science, vol 5631. Springer, Berlin, Heidelberg

Abstract

This paper describes the approach taken to the XML Mining track at INEX 2008 by a group at the Queensland University of Technology. We introduce the K-tree clustering algorithm in an Information Retrieval context by adapting it for document clustering. Many large scale problems exist in document clustering. K-tree scales well with large inputs due to its low complexity. It offers promising results both in terms of efficiency and quality. Document classification was completed using Support Vector Machines.

Keywords

INEX XML Mining Clustering K-tree Tree Vector Quantization Text Classification Support Vector Machine 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Christopher M. De Vries
    • 1
  • Shlomo Geva
    • 1
  1. 1.Faculty of Science and TechnologyQueensland University of TechnologyBrisbaneAustralia

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