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A Hierarchy-Driven Compression Technique for Advanced OLAP Visualization of Multidimensional Data Cubes

  • Alfredo Cuzzocrea
  • Domenico Saccà
  • Paolo Serafino
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4081)

Abstract

In this paper, we investigate the problem of visualizing multidimensional data cubes, and propose a novel technique for supporting advanced OLAP visualization of such data structures. Founding on very efficient data compression solutions for two-dimensional data domains, the proposed technique relies on the amenity of generating “semantics-aware” compressed representation of two-dimensional OLAP views extracted from multidimensional data cubes via the so-called OLAP dimension flattening process. A wide set of experimental results conducted on several kind of synthetic two-dimensional OLAP views clearly confirm the effectiveness and the efficiency of our technique, also in comparison with state-of-the-art proposals.

Keywords

Range Query Data Cube Splitting Position OLAP Query Multidimensional Database 
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

  • Alfredo Cuzzocrea
    • 1
  • Domenico Saccà
    • 1
    • 2
  • Paolo Serafino
    • 1
  1. 1.Department of ElectronicsComputer Science, and Systems University of CalabriaCosenzaItaly
  2. 2.Institute of High Performance Computing and NetworksItalian National Research CouncilCosenzaItaly

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