Top-k query processing in uncertain databases

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Top-k query processing in uncertain databases (2007)

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by Mohamed A. Soliman , Ihab F. Ilyas

Venue:	In ICDE
Citations:	123 - 9 self

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@INPROCEEDINGS{Soliman07top-kquery,
    author = {Mohamed A. Soliman and Ihab F. Ilyas},
    title = {Top-k query processing in uncertain databases},
    booktitle = {In ICDE},
    year = {2007},
    pages = {896--905}
}

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Abstract

Top-k processing in uncertain databases is semantically and computationally different from traditional top-k processing. The interplay between score and uncertainty makes traditional techniques inapplicable. We introduce new probabilistic formulations for top-k queries. Our formulations are based on “marriage ” of traditional top-k semantics and possible worlds semantics. In the light of these formulations, we construct a framework that encapsulates a state space model and efficient query processing techniques to tackle the challenges of uncertain data settings. We prove that our techniques are optimal in terms of the number of accessed tuples and materialized search states. Our experiments show the efficiency of our techniques under different data distributions with orders of magnitude improvement over naïve materialization of possible worlds. 1

Keyphrases

uncertain database top-k query processing accessed tuples top-k query different data distribution efficient query processing technique traditional top-k processing traditional technique na ve materialization search state uncertain data setting new probabilistic formulation magnitude improvement possible world semantics possible world top-k processing traditional top-k semantics state space model

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