Multi-Source skyline queries processing in multi-dimensional space

  • Authors:

  • Cuiping Li;Wenlin He;Hong Chen

  • Affiliations:

  • Key Labs of Data and Knowledge Engineering, MOE, China;Key Labs of Data and Knowledge Engineering, MOE, China;Key Labs of Data and Knowledge Engineering, MOE, China

  • Venue:
  • PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
  • Year:
  • 2010

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Abstract

This paper studies the problem of optimizing skyline queries with respect to multiple sources in the multidimensional space (MDMS skyline). It is challenging to process such kinds of queries efficiently due to the difficulties arising from both multi-source preferences and multi-dimensional analysis. We propose a new query evaluation model, called BitStructure, to answer MDMS skyline queries efficiently. Based on the BitStructure, we develop efficient query algorithms. The main intuition and novelty behind our approaches is that we exploit the unified BitStructure structure to seamlessly integrate multi-dimensional selection and multi-source skyline analysis. Our experimental evaluation using various synthetic datasets demonstrates that the proposed algorithms are efficient and scalable.