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A Structure Preserving Flat Data Format Representation for Tree-Structured Data

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New Frontiers in Applied Data Mining (PAKDD 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7104))

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Abstract

Mining of semi-structured data such as XML is a popular research topic due to many useful applications. The initial work focused mainly on values associated with tags, while most of recent developments focus on discovering association rules among tree structured data objects to preserve the structural information. Other data mining techniques have had limited use in tree-structured data analysis as they were mainly designed to process flat data format with no need to capture the structural properties of data objects. This paper proposes a novel structure-preserving way for representing tree-structured document instances as records in a standard flat data structure to enable applicability of a wider range of data analysis techniques. The experiments using synthetic and real world data demonstrate the effectiveness of the proposed approach.

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Author information

Authors and Affiliations

  1. DEBII, Curtin University, Perth, Australia

    Fedja Hadzic

Authors
  1. Fedja Hadzic
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Editor information

Editors and Affiliations

  1. Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway, PO Box 123, NSW 2007, Sydney, Australia

    Longbing Cao

  2. Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences, 518055, Shenzhen, China

    Joshua Zhexue Huang  & Jun Luo  & 

  3. The University of Melbourne, VIC 3010, Melbourne, Australia

    James Bailey

  4. The University of Auckland, Auckland, New Zealand

    Yun Sing Koh

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Hadzic, F. (2012). A Structure Preserving Flat Data Format Representation for Tree-Structured Data. In: Cao, L., Huang, J.Z., Bailey, J., Koh, Y.S., Luo, J. (eds) New Frontiers in Applied Data Mining. PAKDD 2011. Lecture Notes in Computer Science(), vol 7104. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28320-8_19

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  • DOI: https://doi.org/10.1007/978-3-642-28320-8_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28319-2

  • Online ISBN: 978-3-642-28320-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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