Efficient and scalable method for processing top-k spatial Boolean queries

  • Authors:
  • Ariel Cary;Ouri Wolfson;Naphtali Rishe

  • Affiliations:
  • School of Computing and Information Sciences, Florida International University, Miami, FL;Department of Computer Science, University of Illinois at Chicago, Chicago, IL;School of Computing and Information Sciences, Florida International University, Miami, FL

  • Venue:
  • SSDBM'10 Proceedings of the 22nd international conference on Scientific and statistical database management
  • Year:
  • 2010

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Abstract

In this paper, we present a novel method to efficiently process top-k spatial queries with conjunctive Boolean constraints on textual content. Our method combines an R-tree with an inverted index by the inclusion of spatial references in posting lists. The result is a disk-resident, dual-index data structure that is used to proactively prune the search space. R-tree nodes are visited in best-first order. A node entry is placed in the priority queue if there exists at least one object that satisfies the Boolean condition in the subtree pointed by the entry; otherwise, the subtree is not further explored. We show via extensive experimentation with real spatial databases that our method has increased performance over alternate techniques while scaling to large number of objects.