research-article

Asymptotically efficient algorithms for skyline probabilities of uncertain data

Authors:

Mikhail J. Atallah,

Hao YuanAuthors Info & Claims

ACM Transactions on Database Systems (TODS), Volume 36, Issue 2

Article No.: 12, Pages 1 - 28

https://doi.org/10.1145/1966385.1966390

Published: 02 June 2011 Publication History

Abstract

Skyline computation is widely used in multicriteria decision making. As research in uncertain databases draws increasing attention, skyline queries with uncertain data have also been studied. Some earlier work focused on probabilistic skylines with a given threshold; Atallah and Qi [2009] studied the problem to compute skyline probabilities for all instances of uncertain objects without the use of thresholds, and proposed an algorithm with subquadratic time complexity. In this work, we propose a new algorithm for computing all skyline probabilities that is asymptotically faster: worst-case O(n √n log n) time and O(n) space for 2D data; O(n^2−1/d log^d−1 n) time and O(n log^d−2 n) space for d-dimensional data. Furthermore, we study the online version of the problem: Given any query point p (unknown until the query time), return the probability that no instance in the given data set dominates p. We propose an algorithm for answering such an online query for d-dimensional data in O(n^1−1/d log^d−1 n) time after preprocessing the data in O(n^2−1/d log^d−1) time and space.

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Cited By

Gao XLi JMiao D(2024)Computing All Restricted Skyline Probabilities on Uncertain Datasets2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00363(4773-4786)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDE60146.2024.00363
Agrawal ALi YXue JJanardan R(2020)The most-likely skyline problem for stochastic pointsComputational Geometry10.1016/j.comgeo.2020.101609(101609)Online publication date: Jan-2020
https://doi.org/10.1016/j.comgeo.2020.101609
Rao Kagita VPujari APadmanabhan VKumar V(2019)Skyline Recommendation with Uncertain PreferencesPattern Recognition Letters10.1016/j.patrec.2019.06.002Online publication date: Jun-2019
https://doi.org/10.1016/j.patrec.2019.06.002
Show More Cited By

Index Terms

Asymptotically efficient algorithms for skyline probabilities of uncertain data
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. Database query processing
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory
      1. Database query processing and optimization (theory)

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cover image ACM Transactions on Database Systems

ACM Transactions on Database Systems Volume 36, Issue 2

May 2011

257 pages

ISSN:0362-5915

EISSN:1557-4644

DOI:10.1145/1966385

Issue’s Table of Contents

Copyright © 2011 ACM.

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Association for Computing Machinery

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Publication History

Published: 02 June 2011

Accepted: 01 February 2011

Revised: 01 December 2010

Received: 01 May 2010

Published in TODS Volume 36, Issue 2

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Division of Computing and Communication Foundations
Qtar National Research
Division of Computer and Network Systems
City University of Hong Kong

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Cited By

Gao XLi JMiao D(2024)Computing All Restricted Skyline Probabilities on Uncertain Datasets2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00363(4773-4786)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDE60146.2024.00363
Agrawal ALi YXue JJanardan R(2020)The most-likely skyline problem for stochastic pointsComputational Geometry10.1016/j.comgeo.2020.101609(101609)Online publication date: Jan-2020
https://doi.org/10.1016/j.comgeo.2020.101609
Rao Kagita VPujari APadmanabhan VKumar V(2019)Skyline Recommendation with Uncertain PreferencesPattern Recognition Letters10.1016/j.patrec.2019.06.002Online publication date: Jun-2019
https://doi.org/10.1016/j.patrec.2019.06.002
Gao YMiao X(2018)Query Processing over Incomplete DatabasesSynthesis Lectures on Data Management10.2200/S00870ED1V01Y201807DTM05010:2(1-122)Online publication date: 13-Aug-2018
https://doi.org/10.2200/S00870ED1V01Y201807DTM050
Yang ZLi KZhou XMei JGao Y(2018)Top k probabilistic skyline queries on uncertain dataNeurocomputing10.1016/j.neucom.2018.03.052317(1-14)Online publication date: Nov-2018
https://doi.org/10.1016/j.neucom.2018.03.052
Meneghetti N(2018)Probabilistic SkylinesEncyclopedia of Database Systems10.1007/978-1-4614-8265-9_80683(2845-2847)Online publication date: 7-Dec-2018
https://doi.org/10.1007/978-1-4614-8265-9_80683
Huang LLi JKlein P(2017)Stochastic k-center and j-flat-center problemsProceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete Algorithms10.5555/3039686.3039694(110-129)Online publication date: 16-Jan-2017
https://dl.acm.org/doi/10.5555/3039686.3039694
Meneghetti N(2017)Probabilistic SkylinesEncyclopedia of Database Systems10.1007/978-1-4899-7993-3_80683-1(1-3)Online publication date: 16-Jan-2017
https://doi.org/10.1007/978-1-4899-7993-3_80683-1
Li XRen KLi XYu J(2017)Efficient skyline computation over distributed interval dataConcurrency and Computation: Practice and Experience10.1002/cpe.407529:10Online publication date: 28-Mar-2017
https://doi.org/10.1002/cpe.4075
Miao XGao YChen GZhang T(2016)k-dominant skyline queries on incomplete dataInformation Sciences: an International Journal10.1016/j.ins.2016.07.034367:C(990-1011)Online publication date: 1-Nov-2016
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