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International Conference on Extending Database Technology

EDBT 2006: Advances in Database Technology - EDBT 2006 pp 718–736Cite as

On Fast Non-metric Similarity Search by Metric Access Methods

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3896))

Abstract

The retrieval of objects from a multimedia database employs a measure which defines a similarity score for every pair of objects. The measure should effectively follow the nature of similarity, hence, it should not be limited by the triangular inequality, regarded as a restriction in similarity modeling. On the other hand, the retrieval should be as efficient (or fast) as possible. The measure is thus often restricted to a metric, because then the search can be handled by metric access methods (MAMs). In this paper we propose a general method of non-metric search by MAMs. We show the triangular inequality can be enforced for any semimetric (reflexive, non-negative and symmetric measure), resulting in a metric that preserves the original similarity orderings (retrieval effectiveness). We propose the TriGen algorithm for turning any black-box semimetric into (approximated) metric, just by use of distance distribution in a fraction of the database. The algorithm finds such a metric for which the retrieval efficiency is maximized, considering any MAM.

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Author information

Authors and Affiliations

  1. FMP, Department of Software Engineering, Charles University in Prague, Malostranské nám. 25, 118 00, Prague 1, Czech Republic

    Tomáš Skopal

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  1. Tomáš Skopal
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Editor information

Editors and Affiliations

  1. University of Athens, Greece

    Yannis Ioannidis

  2. University of Konstanz, P.O.Box D188, 78457, Konstanz, Germany

    Marc H. Scholl

  3. Sustainable Content Logistics Centre, Hamburg, Germany

    Joachim W. Schmidt

  4. Chair of Software Engineering for Business Information Systems, Technische Universität München, Boltzmannstraße 3, 85748, Garching b. München,  

    Florian Matthes

  5. Department of Informatics, University of Athens Panepistimiopolis, 15771, Athens, Greece

    Mike Hatzopoulos

  6. IPD, Universität Karlsruhe, Am Fasanengarten 5, 76131, Karlsruhe,  

    Klemens Boehm

  7. TU München, D-85748, Garching, Germany

    Alfons Kemper

  8. Technische Universität München, Germany

    Torsten Grust

  9. Institute for Computer Science, Ludwig-Maximilians Universität München,  

    Christian Boehm

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© 2006 Springer-Verlag Berlin Heidelberg

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Skopal, T. (2006). On Fast Non-metric Similarity Search by Metric Access Methods. In: Ioannidis, Y., et al. Advances in Database Technology - EDBT 2006. EDBT 2006. Lecture Notes in Computer Science, vol 3896. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11687238_43

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  • DOI: https://doi.org/10.1007/11687238_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-32960-2

  • Online ISBN: 978-3-540-32961-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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