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Probabilistic Aggregates

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Foundations of Intelligent Systems (ISMIS 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2366))

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Abstract

Though extensions of the relational model of data have been proposed to handle probabilistic information, there has been no work to date on handling aggregate operators in such databases. In this paper, we show how classical aggregation operators (like COUNT, SUM, etc.) as well as other statistical operators (like weighted average, variance, etc.) can be defined as well as implemented over probabilistic databases. We define these operations, develop a formal linear program model for computing answers to such queries, and then develop a generic algorithm to compute aggregates.

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Author information

Authors and Affiliations

  1. University of Maryland, College Park, MD, 20742, USA

    Robert Ross & V. S. Subrahmanian

  2. Towson University, Towson, MD, 21252, USA

    John Grant

Authors
  1. Robert Ross
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  2. V. S. Subrahmanian
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  3. John Grant
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Editor information

Editors and Affiliations

  1. UFR d’Informatique, Université Claude Bernard Lyon I, 8, boulevard Niels Bohr, 69622, Villeurbanne Cedex, France

    Mohand-Saïd Hacid

  2. Dept. of Computer Science College of IT, University of North Carolina, Charlotte, NC, 28223, USA

    Zbigniew W. Raś

  3. Băt. L. Equipe de Recherche en Ingénierie des Connaissances, Université Lumière Lyon 2, 5, avenue Pierre Mendes-France, 69676, Bron Cedex, France

    Djamel A. Zighed

  4. LRI, Université Paris Sud, Băt. 490, 91405, Orsay Cedex, France

    Yves Kodratoff

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© 2002 Springer-Verlag Berlin Heidelberg

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Ross, R., Subrahmanian, V.S., Grant, J. (2002). Probabilistic Aggregates. In: Hacid, MS., Raś, Z.W., Zighed, D.A., Kodratoff, Y. (eds) Foundations of Intelligent Systems. ISMIS 2002. Lecture Notes in Computer Science(), vol 2366. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48050-1_59

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  • DOI: https://doi.org/10.1007/3-540-48050-1_59

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43785-7

  • Online ISBN: 978-3-540-48050-1

  • eBook Packages: Springer Book Archive

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