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An approximate oracle for distance in metric spaces

  • Session III
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Combinatorial Pattern Matching (CPM 1998)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1448))

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Abstract

In this paper we present a new data structure for estimating distances in a pseudo-metric space. Given are a database of objects and a distance function for the objects, which is a pseudo-metric. We map the objects to vectors in a pseudo-Euclidean space with a reasonably low dimension while preserving the distance between two objects approximately. Such a data structure can be used as an approximate oracle to process a broad class of pattern-matching based queries. Experimental results on both synthetic and real data show the good performance of the oracle in distance estimation.

Work supported in part by the Natural Sciences and Engineering Research Council of Canada under Grant No. OGP0046373, and by the U.S. NSF grants IRI-9224601, IRI-9224602, IRI-9531548 and IRI-9531554.

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Authors and Affiliations

  1. Department of Mathematics, Beijing Institute of Light Industry, 11 Fucheng Road, 100037, Beijing, China

    Yanling Yang

  2. Department of Computer Science, The University of Western Ontario, N6A 5B7, London, Ontario, Canada

    Kaizhong Zhang

  3. Department of CIS, New Jersey Institute of Technology, 07102, Newark, NJ, USA

    Xiong Wang

  4. Department of CIS, New Jersey Institute of Technology, 07102, Newark, NJ, USA

    Jason T. L. Wang

  5. Courant Institute of Mathematical Sciences, New York University, 251 Mercer Street, 10012, New York, USA

    Dennis Shasha

Authors
  1. Yanling Yang
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  2. Kaizhong Zhang
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  3. Xiong Wang
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  4. Jason T. L. Wang
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  5. Dennis Shasha
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Martin Farach-Colton

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© 1998 Springer-Verlag Berlin Heidelberg

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Yang, Y., Zhang, K., Wang, X., Wang, J.T.L., Shasha, D. (1998). An approximate oracle for distance in metric spaces. In: Farach-Colton, M. (eds) Combinatorial Pattern Matching. CPM 1998. Lecture Notes in Computer Science, vol 1448. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0030784

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  • DOI: https://doi.org/10.1007/BFb0030784

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64739-3

  • Online ISBN: 978-3-540-69054-2

  • eBook Packages: Springer Book Archive

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