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Query Planning with Information Quality Bounds

  • Ulf Leser
  • Felix Naumann
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 7)

Abstract

Query planning for information integration using a local-as-view approach is exponential in the size of the user query. Furthermore, it may generate an exponential number of plans, many of which will produce results of very poor quality. We propose to use information quality reasoning to speed up query planning. We construct tight upper quality bounds for a branch & bound algorithm. The algorithm uses these quality scores to filter out non-promising plans early on. Experiments show that this approach dramatically improves planning time without compromising the quality of the result.

Keywords

Information Quality User Query Query Planning Compatibility Test Correct Plan 
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 2001

Authors and Affiliations

  • Ulf Leser
    • 1
  • Felix Naumann
    • 2
  1. 1.University of TechnologyBerlinGermany
  2. 2.Humboldt UniversityBerlinGermany

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