Query Pre-processing of Topological Constraints: Comparing a Composition-Based with Neighborhood-Based Approach

  • M. Andrea Rodríguez
  • Max J. Egenhofer
  • Andreas D. Blaser
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2750)


This paper derives and compares two strategies for minimizing topological constraints in a query expressed by a visual example: (1) elimination of topological relations that are implied uniquely by composition and (2) restriction to topological relations that relate near-neighbor objects, as determined by a Delaunay triangulation. In both cases, the query processing approach is to solve a constraint satisfaction problem over a graph of binary topological relations. Individuals and the combination of the composition- and neighborhood-based strategies were implemented and compared with respect to their ability to reduce topological constraints, and with respect to the quality of the results obtained by a similarity-based searching that uses these pre-processing strategies. The main conclusion of this work is that similarity queries that are formulated in a visual language should exploit the metric characteristics of the configuration, even if only topological constraints are considered for making matches.


Query Processing Delaunay Triangulation Constraint Satisfaction Problem Spatial Object Topological Relation 
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

  • M. Andrea Rodríguez
    • 1
  • Max J. Egenhofer
    • 2
    • 3
  • Andreas D. Blaser
    • 4
  1. 1.Department of Information Engineering and Computer ScienceUniversity of ConcepciónConcepciónChile
  2. 2.National Center for Geographic Information and AnalysisUniversity of MaineOronoUSA
  3. 3.Department of Information ScienceUniversity of MaineOronoUSA
  4. 4.Environmental Systems Research InstituteRedlandsUSA

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