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ISSA: Efficient Skyline Computation for Incomplete Data

  • Kaiqi ZhangEmail author
  • Hong Gao
  • Hongzhi Wang
  • Jianzhong Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9645)

Abstract

Over the past years, the skyline query has already caused wide attention in database community. For the skyline computation over incomplete data, the existing algorithms focus mainly on reducing the dominance tests among these points with the same bitmap representation by exploiting \( Bucket \) technique. While, the issue of exhaustive comparisons among those points in different buckets remains unsolved, which is the major cost. In this paper, we present a general framework COBO for skyline computation over incomplete data. And based on COBO, we develop an efficient algorithm ISSA in two phases: \( pruning \) \( compared \) \( list \) and \( reducing \) \( expected \) \( comparison \) \( times \). We construct a compared list order according to ACD to diminish significantly the total comparisons among the points in different buckets. The experimental evaluation on synthetic and real data sets indicates that our algorithm outperforms existing state-of-the-art algorithm 1 to 2 orders of magnitude in comparisons.

Keywords

Incomplete Data Skyline Query Skyline Point Dominance Test Skyline Computation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Kaiqi Zhang
    • 1
    Email author
  • Hong Gao
    • 1
  • Hongzhi Wang
    • 1
  • Jianzhong Li
    • 1
  1. 1.School of Computer Science and TechnologyHarbin Institute of TechnologyHarbinChina

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