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International Conference on Knowledge Engineering and Knowledge Management

EKAW 2004: Engineering Knowledge in the Age of the Semantic Web pp 492–493Cite as

Computing Similarity Between XML Documents for XML Mining

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3257))

Abstract

The self-describing feature of XML offers both challenges and opportunities in document management and data mining. We propose new metric for computing similarity between XML documents for XML mining.

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References

  1. Lee, J.W., Lee, K., Kim, W.: Preparations for Semantics-based XML Mining. In: Proc. of IEEE International Conference on Data Mining (ICDM), pp. 345–352 (November/December 2001)

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Author information

Authors and Affiliations

  1. Dept. of Computer Science and Engineering, Ewha Womans University, 11-1 Daehyun-dong, Sudaemun-ku, Seoul, Korea

    Jung-Won Lee & Seung-Soo Park

Authors
  1. Jung-Won Lee
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  2. Seung-Soo Park
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Editor information

Editors and Affiliations

  1. Knowledge Media Institute, The Open University, Milton Keynes, UK

    Enrico Motta

  2. Electronics and Computer Science, University of Southampton, UK

    Nigel R Shadbolt

  3. Knowledge Media Institute, Open University, UK

    Arthur Stutt

  4. University of Southampton, SO17 1BJ, Southampton, UK

    Nick Gibbins

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© 2004 Springer-Verlag Berlin Heidelberg

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Cite this paper

Lee, JW., Park, SS. (2004). Computing Similarity Between XML Documents for XML Mining. In: Motta, E., Shadbolt, N.R., Stutt, A., Gibbins, N. (eds) Engineering Knowledge in the Age of the Semantic Web. EKAW 2004. Lecture Notes in Computer Science(), vol 3257. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30202-5_42

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  • DOI: https://doi.org/10.1007/978-3-540-30202-5_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23340-4

  • Online ISBN: 978-3-540-30202-5

  • eBook Packages: Springer Book Archive

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