• DocumentCode
    2097122
  • Title

    XCLSC: Structure and content-based clustering of XML documents

  • Author

    Bessine, Karima ; Nehar, Attia ; Cherroun, Hadda ; Moussaoui, Abdelouahab

  • Author_Institution
    Laboratoire d´Informatique et Mathématiques Université Amar Télidji Laghouat, Algérie
  • fYear
    2015
  • fDate
    28-30 April 2015
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    This paper proposes a novel Clustering approach for XML documents that combines both their content and structure information using tree structural-content summaries in order to reduce the size of the document. This reduction has twofold purpose. First, it reduces the size of the XML tree by eliminating redundant nodes. Second, it gathers similaire content. The clustering is performed according to a similarity measure that takes into account the structure and the content between levels. Several experiments are performed to explore the effectiveness of using tree structural summaries and constrained content in the clustering process. Empirical analysis reveals that the designed clustering approach using content within structure and tree structural summaries gives a better solution for XML clustering while improving runtime. It is very suitable when we deal with big data sets.
  • Keywords
    Big data; Clustering algorithms; Data structures; Electronic mail; Entropy; Information services; XML; Clustering; Level Structure-Content; Structural Summary; XML documents;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Programming and Systems (ISPS), 2015 12th International Symposium on
  • Conference_Location
    Algiers, Algeria
  • Type

    conf

  • DOI
    10.1109/ISPS.2015.7244989
  • Filename
    7244989