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Estimating Proximity of Metric Ball Regions for Multimedia Data Indexing

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Advances in Information Systems (ADVIS 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1909))

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Abstract

The problem of defining and computing proximity of regions constraining objects from generic metric spaces is investigated. Approximate, computationally fast, approach is developed for pairs of metric ball regions, which covers the needs of current systems for processing data through distances. The validity and precision of proposed solution is verified by extensive simulation on three substantially different data files. The precision of obtained results is very satisfactory. Besides other possibilities, the proximity measure can be applied to improve the performance of metric trees, developed for multimedia similarity search indexing. Specific system areas concern splitting and merging of regions, pruning regions during similarity retrieval, ranking regions for best case matching, and declustering regions to achieve parallelism.

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References

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Author information

Authors and Affiliations

  1. IEI-CNR, Pisa, Italy

    Giuseppe Amato & Pasquale Savino

  2. CNUCE-CNR, Pisa, Italy

    Fausto Rabitti

  3. Masaryk University, Brno, Czech Republic

    Pavel Zezula

Authors
  1. Giuseppe Amato
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  2. Fausto Rabitti
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  3. Pasquale Savino
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  4. Pavel Zezula
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Editor information

Editors and Affiliations

  1. Computer Engineering Department, Dokuz Eylul University, Bornova, 35100, Izmir, Turkey

    Tatyana Yakhno

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© 2000 Springer-Verlag Berlin Heidelberg

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Amato, G., Rabitti, F., Savino, P., Zezula, P. (2000). Estimating Proximity of Metric Ball Regions for Multimedia Data Indexing. In: Yakhno, T. (eds) Advances in Information Systems. ADVIS 2000. Lecture Notes in Computer Science, vol 1909. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-40888-6_7

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  • DOI: https://doi.org/10.1007/3-540-40888-6_7

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41184-0

  • Online ISBN: 978-3-540-40888-8

  • eBook Packages: Springer Book Archive

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