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Evaluation of Iceberg Distance Joins

  • Yutao Shou
  • Nikos Mamoulis
  • Huiping Cao
  • Dimitris Papadias
  • David W. Cheung
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2750)

Abstract

The iceberg distance join returns object pairs within some distance from each other, provided that the first object appears at least a number of times in the result, e.g., “find hotels which are within 1km to at least 10 restaurants”. The output of this query is the subset of the corresponding distance join (e.g., “find hotels which are within 1km to some restaurant”) that satisfies the additional cardinality constraint. Therefore, it could be processed by using a conventional spatial join algorithm and then filtering-out the non-qualifying pairs. This approach, however, is expensive, especially when the cardinality constraint is highly selective. In this paper, we propose output-sensitive algorithms that prune the search space by integrating the cardinality with the distance constraint. We deal with cases of indexed/non-indexed datasets and evaluate the performance of the proposed techniques with extensive experimental evaluation covering a wide range of problem parameters.

Keywords

Priority Queue Node Pair Cardinality Constraint Close Pair Node Entry 
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-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Yutao Shou
    • 1
  • Nikos Mamoulis
    • 1
  • Huiping Cao
    • 1
  • Dimitris Papadias
    • 2
  • David W. Cheung
    • 1
  1. 1.Department of Computer Science and Information SystemsUniversity of Hong KongHong Kong
  2. 2.Department of Computer ScienceHong Kong University of Science and TechnologyHong Kong

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