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Querying Compressed XML Data

  • Conference paper
Book cover Trends and Applications in Knowledge Discovery and Data Mining (PAKDD 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7867))

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Abstract

The exploitation of large volume of XML (eXtensible Markup Language) data with a limited storage space implies the development of a special and reliable treatment to compress data and query them. This work studies and treats these processes in order to combine them via a mediator while facilitating querying compressed XML data without recourse to the decompression process. We propose a new technique to compress, re-index and query XML data while improving XMill and B+Tree algorithms. We show the reliability and the speed up of the proposed querying system towards response time and answers’ exactitude.

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Author information

Authors and Affiliations

  1. Ecole Nationale d’Ingénieurs de Tunis, Université Tunis El Manar, BP. 37. Le Belvèdère 1002, Tunis, Tunisia

    Olfa Arfaoui & Minyar Sassi-Hidri

Authors
  1. Olfa Arfaoui
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  2. Minyar Sassi-Hidri
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Editor information

Editors and Affiliations

  1. School of Information Technology and Mathematical Sciences, University of South Australia, 1 Mawson Lakes Boulevard, 5095, Adelaide, SA, Australia

    Jiuyong Li

  2. Advanced Analytics Institute, University of Technology, 2-12 Blackfriars Street, Chippendale, Blackfriars Campus, 2008, Sydney, NSW, Australia

    Longbing Cao  & Can Wang  & 

  3. Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, 117576, Singapore, Singapore

    Kay Chen Tan

  4. School of Automation, Guangdong University of Technology, No. 100 Waihuan Xi Road, Panyu District, 510006, Guangzhou, China

    Bo Liu

  5. School of Computing Science, Simon Fraser University, 8888 University Drive, V5A 1S6, Burnaby, BC, Canada

    Jian Pei

  6. Department of Computer Science and Information Engineering, National Cheng Kung University, No.1, University Road, 701, Tainan, Taiwan

    Vincent S. Tseng

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Arfaoui, O., Sassi-Hidri, M. (2013). Querying Compressed XML Data. In: Li, J., et al. Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2013. Lecture Notes in Computer Science(), vol 7867. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40319-4_42

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  • DOI: https://doi.org/10.1007/978-3-642-40319-4_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40318-7

  • Online ISBN: 978-3-642-40319-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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