• DocumentCode
    131005
  • Title

    Skyline query on uncertain data based on improved probabilistic constraint space algorithm

  • Author

    Dong Liming ; Liu Qing Bao ; Dai Changhua

  • Author_Institution
    Sci. & Technol. on Inf. Syst. Eng. Lab., Nat. Univ. of Defense Technol., Changsha, China
  • fYear
    2014
  • fDate
    27-29 June 2014
  • Firstpage
    929
  • Lastpage
    932
  • Abstract
    PCS algorithm is a non-indexing method to prune non-skyline objects. Its pruning rate is more than 90% when data dimension is no more than 4, however when data dimension exceeds 4 the pruning rate falls significantly. This article improved PCS algorithm to improve the pruning rate of high-dimension case. The main idea of PCS is to prune the non-skyline objects by establishing the minimum probabilistic constraint space. Experiments and analysis prove that IPCS improved an average 10% increase in the pruning rate.
  • Keywords
    Pareto analysis; data handling; probability; query processing; PCS algorithm; Pareto; data dimension; minimum probabilistic constraint space; nonindexing method; nonskyline object pruning; probabilistic constraint space algorithm; skyline query; uncertain data; Buildings; Educational institutions; Indexing; Laboratories; Probabilistic logic; Probability; IPCS; PCS; Skyline; uncertain data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
  • Conference_Location
    Beijing
  • ISSN
    2327-0586
  • Print_ISBN
    978-1-4799-3278-8
  • Type

    conf

  • DOI
    10.1109/ICSESS.2014.6933717
  • Filename
    6933717