Efficient general spatial skyline computation

  • Authors:

  • Qianlu Lin;Ying Zhang;Wenjie Zhang;Xuemin Lin

  • Affiliations:

  • School of Computer Science & Engineering, University of New South Wales, Sydney, Australia 2052;School of Computer Science & Engineering, University of New South Wales, Sydney, Australia 2052;School of Computer Science & Engineering, University of New South Wales, Sydney, Australia 2052;School of Computer Science & Engineering, University of New South Wales, Sydney, Australia 2052

  • Venue:
  • World Wide Web
  • Year:
  • 2013

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Abstract

With the emergence of location-aware mobile device technologies, communication technologies and GPS systems, the location based queries have attracted great attentions in the database literature. In many user recommendation web services, the spatial preference query is used to suggest the objects based on their spatial proximity with the facilities. In this paper, we study the problem of general spatial skyline (GSSKY) which can provide the minimal candidate set of the optimal solutions for any monotonic distance based spatial preference query. Efficient progressive algorithm called P-GSSKY is proposed to significantly reduce the number of non-promising objects in the computation. Moreover, we also propose spatial join based algorithm, called J-GSSKY, which can compute GSSKY efficiently in terms of I/O cost. The paper conducts a comprehensive performance study of the proposed techniques based on both real and synthetic data.