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A Framework for Clustering and Dynamic Maintenance of XML Documents

  • Ahmed Al-Shammari
  • Chengfei Liu
  • Mehdi Naseriparsa
  • Bao Quoc Vo
  • Tarique Anwar
  • Rui Zhou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10604)

Abstract

Web data clustering has been widely studied in the data mining communities. However, dynamic maintenance of the web data clusters is still a challenging task. In this paper, we propose a novel framework called XClusterMaint which serves for both clustering and maintenance of the XML documents. For clustering, we take both structure and content into account and propose an efficient solution for grouping the documents based on the combination of structure and content similarity. For maintenance, we propose an incremental approach for maintaining the existing clusters dynamically when we receive new incoming XML documents. Since the dynamic maintenance of the clusters is computationally expensive, we also propose an improved approach which uses a lazy maintenance scheme to improve the performance of the clusters maintenance. The experimental results on real datasets verify the efficiency of the proposed clustering and maintenance model.

Keywords

Clustering XML documents Structure and content similarity Dynamic maintenance 

Notes

Acknowledgements

This work was partially supported by the ARC Discovery Project under Grant No. DP170104747 and the Iraqi Ministry of Higher Education and Scientific Research.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Ahmed Al-Shammari
    • 1
  • Chengfei Liu
    • 1
  • Mehdi Naseriparsa
    • 1
  • Bao Quoc Vo
    • 1
  • Tarique Anwar
    • 1
  • Rui Zhou
    • 1
  1. 1.Swinburne University of TechnologyMelbourneAustralia

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