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A Top-k Filter for Logic-Based Similarity Conditions on Probabilistic Databases

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Advances in Databases and Information Systems (ADBIS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7503))

Abstract

Probabilistic databases have been established as a powerful technique for managing and analysing large uncertain data sets. A major challenge for probabilistic databases is query evaluation. There exist even simple relational queries for which the exact probability computation is \(\#\mathcal{P}\)-hard. Consequently, if we are only interested in the k highest ranked tuples, then an efficient pre-filtering can reduce the computation time significantly. In this work we present a top-k filter which computes a small candidate set for a top-k answer based on a complex relational query in polynomial time.

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Author information

Authors and Affiliations

  1. Institute of Computer Science, Brandenburg University of Technology Cottbus, Postfach 10 13 44, D-03013, Cottbus, Germany

    Sebastian Lehrack & Sascha Saretz

Authors
  1. Sebastian Lehrack
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  2. Sascha Saretz
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Editor information

Editors and Affiliations

  1. Institute of Computing Science, Poznań University of Technology, Piotrowo 2, 60-965, Poznań, Poland

    Tadeusz Morzy

  2. Department of Computer Science, AG DBIS, University of Kaiserslautern, Germany, P.O. Box 3049, 67653, Kaiserslautern, Germany

    Theo Härder

  3. Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60-965, Poznan, Poland

    Robert Wrembel

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Lehrack, S., Saretz, S. (2012). A Top-k Filter for Logic-Based Similarity Conditions on Probabilistic Databases. In: Morzy, T., Härder, T., Wrembel, R. (eds) Advances in Databases and Information Systems. ADBIS 2012. Lecture Notes in Computer Science, vol 7503. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33074-2_20

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  • DOI: https://doi.org/10.1007/978-3-642-33074-2_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33073-5

  • Online ISBN: 978-3-642-33074-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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