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A Visual Evaluation Framework for Spatial Pruning Methods

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Advances in Spatial and Temporal Databases (SSTD 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6849))

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Abstract

Over the past years, several pruning criteria for spatial objects have been proposed that are commonly used during the processing of similarity queries. Each of these criteria have different properties and pruning areas. This demo offers a visual interface for comparing existing pruning criteria under various settings and in different applications allowing an easy integration of new criteria. Thus, the proposed software helps to evaluate and understand the strengths and weaknesses of pruning criteria for arbitrary spatial similarity queries.

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References

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  3. Emrich, T., Kriegel, H.P., Kröger, P., Renz, M., Züfle, A.: Boosting spatial pruning: On optimal pruning of MBRs. In: Proc. SIGMOD (2010)

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Author information

Authors and Affiliations

  1. Institute for Informatics, Ludwig-Maximilians-Universität München, Oettingenstr, 67, D-80538, München, Germany

    Tobias Emrich, Hans-Peter Kriegel, Peer Kröger, Matthias Renz, Johannes Senner & Andreas Züfle

Authors
  1. Tobias Emrich
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  2. Hans-Peter Kriegel
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  3. Peer Kröger
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  4. Matthias Renz
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  5. Johannes Senner
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  6. Andreas Züfle
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Editor information

Editors and Affiliations

  1. Institute for the Management of Information Systems, Research Center “ATHENA”, G.Mpakou 17, 11524, Athens, Greece

    Dieter Pfoser

  2. Department of Computer Science and Engineering, Chinese University of Hong Kong, Sha Tin, New Territories, Hong Kong SAR, China

    Yufei Tao

  3. School of Information Systems, Singapore Management University, 80 Stamford Road, 178902, Singapore

    Kyriakos Mouratidis

  4. Department of Computing Science, ATH University of Alberta, T6G 2E8, Edmonton, Alberta, Canada

    Mario A. Nascimento

  5. Department of Computer Science and Engineering, University of Minnesota, 4-192, 200 Union St. SE, Minneapolis, MN, USA

    Mohamed Mokbel  & Shashi Shekhar  & 

  6. Department of Computer Science and Engineering, University of North Texas, 3040 North Elm, Denton, TX, USA

    Yan Huang

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© 2011 Springer-Verlag Berlin Heidelberg

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Cite this paper

Emrich, T., Kriegel, HP., Kröger, P., Renz, M., Senner, J., Züfle, A. (2011). A Visual Evaluation Framework for Spatial Pruning Methods. In: Pfoser, D., et al. Advances in Spatial and Temporal Databases. SSTD 2011. Lecture Notes in Computer Science, vol 6849. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22922-0_40

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  • DOI: https://doi.org/10.1007/978-3-642-22922-0_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22921-3

  • Online ISBN: 978-3-642-22922-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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