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Efficiently Computing and Querying Multidimensional OLAP Data Cubes over Probabilistic Relational Data

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Advances in Databases and Information Systems (ADBIS 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6295))

Abstract

Focusing on novel database application scenarios, where datasets arise more and more in uncertain and imprecise formats, in this paper we propose a novel framework for efficiently computing and querying multidimensional OLAP data cubes over probabilistic data, which well-capture previous kinds of data. Several models and algorithms supported in our proposed framework are formally presented and described in details, based on well-understood theoretical statistical/probabilistic tools, which converge to the definition of the so-called probabilistic OLAP data cubes, the most prominent result of our research. Finally, we complete our analytical contribution by introducing an innovative Probability Distribution Function (PDF)-based approach for efficiently querying probabilistic OLAP data cubes.

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Author information

Authors and Affiliations

  1. ICAR-CNR and University of Calabria, Italy

    Alfredo Cuzzocrea

  2. Dept. of Informatics and Telecommunications, University of Athens, Greece

    Dimitrios Gunopulos

Authors
  1. Alfredo Cuzzocrea
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  2. Dimitrios Gunopulos
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Editor information

Editors and Affiliations

  1. Department of Computer and Infoamtion Science, University of Genova, Via Dodecaneso, 35, 16146, Genova, Italy

    Barbara Catania

  2. Faculty of Science, Department of Mathematics and Informatics, University of Novi Sad, Trg Dositeja Obradovica 4, 21000, Novi Sad, Serbia

    Mirjana Ivanović

  3. Institute of Computer Science and Applied Mathematics, Christian-Albrechts-University of Kiel, Olshausenstr. 40, 24098, Kiel, Germany

    Bernhard Thalheim

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Cuzzocrea, A., Gunopulos, D. (2010). Efficiently Computing and Querying Multidimensional OLAP Data Cubes over Probabilistic Relational Data. In: Catania, B., Ivanović, M., Thalheim, B. (eds) Advances in Databases and Information Systems. ADBIS 2010. Lecture Notes in Computer Science, vol 6295. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15576-5_12

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  • DOI: https://doi.org/10.1007/978-3-642-15576-5_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15575-8

  • Online ISBN: 978-3-642-15576-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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