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Mining Changes from Versions of Dynamic XML Documents

  • Laura Irina Rusu
  • Wenny Rahayu
  • David Taniar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3915)

Abstract

The ability to store information contained in XML documents for future reference becomes a very important issue these days, as the number of applications which use and exchange data in XML format is growing continuously. Moreover, the contents of XML documents are dynamic and they change across time, so researchers are looking to efficient solutions to store the documents’ versions and eventually extract interesting information out of them. This paper proposes a novel approach for mining association rules from changes between versions of dynamic XML documents, in a simple manner, by using the information contained in the consolidated delta. We argue that by applying our proposed algorithm, important information about the behaviour of the changed XML document in time could be extracted and then used to make predictions about its future performance.

Keywords

Association Rule Minimum Support Mining Association Rule Historic Version Unordered Tree 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Laura Irina Rusu
    • 1
  • Wenny Rahayu
    • 1
  • David Taniar
    • 2
  1. 1.Department of Computer Science & Computer EngLaTrobe UniversityAustralia
  2. 2.School of Business SystemsMonash UniversityClaytonAustralia

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