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Encyclopedia of Database Systems pp 1–5Cite as

Uncertain Top-k Queries

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Synonyms

Probabilistic ranking; Probabilistic top-k queries; Uncertain top-k queries

Definition

Given a relation R and a scoring function F that assigns a numeric score to each tuple in R, a top-k query returns the k tuples in R with the top ranks according to the scores computed by F. An uncertain top-k query is a top-k query where uncertainty (probabilistic) models are used to describe either R, F, or both R and F. Integrating the semantics of ranking and uncertainty models results in defining a probability distribution on the possible ranks of a given tuple in R according to F. Different formulations of uncertain top-k queries arise from such interplay between scoring and probabilistic measures. Query processing algorithms aim at minimizing the needed score and probabilistic computation by exploiting available data access paths and probabilistic early termination criteria.

Historical Background

Many uncertain/probabilistic data models adopt possible world semantics, where an...

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Recommended Reading

  1. Cormode G, Li F, Yi K. Semantics of ranking queries for probabilistic data and expected Ranks. ICDE 2009.

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  2. Dalvi N, Suciu D. Efficient query evaluation on probabilistic databases. VLDB J, 2007.

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  4. Hua M, Pei J, Zhang W, Lin X. Ranking queries on uncertain data: a probabilistic threshold approach. SIGMOD, 2008.

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  5. Li J, Saha B, Deshpande A. A unified approach to ranking in probabilistic databases. VLDB, 2009.

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  6. Soliman M, Ilyas I, Chang K. Top-k query processing in uncertain databases. ICDE, 2007.

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  7. Soliman M, Ilyas I, Chang K. Probabilistic top-k and ranking-aggregate queries. ACM TODS, 2008.

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  8. Soliman M, Ilyas I. Ranking with Uncertain Scores. ICDE, 2009.

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  9. Soliman M, Ilyas I, Martinenghi D, Tagliasacchi M. Ranking with uncertain scoring functions: semantics and sensitivity measures. SIGMOD 2011.

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  10. Zhang X, Chomicki J. Semantics and evaluation of top-k queries in probabilistic databases. Distributed and Parallel Databases, 2009.

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Author information

Authors and Affiliations

  1. Datometry Inc., San Francisco, CA, USA

    Mohamed A. Soliman

Authors
  1. Mohamed A. Soliman
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Corresponding author

Correspondence to Mohamed A. Soliman .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, Georgia, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, Ontario, Canada

    M. Tamer Özsu

Section Editor information

  1. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada

    Ihab Ilyas

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© 2016 Springer Science+Business Media LLC

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Soliman, M.A. (2016). Uncertain Top-k Queries. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_80686-1

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  • DOI: https://doi.org/10.1007/978-1-4899-7993-3_80686-1

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  • Publisher Name: Springer, New York, NY

  • Online ISBN: 978-1-4899-7993-3

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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