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International Symposium on Algorithms and Computation

ISAAC 2004: Algorithms and Computation pp 522–533Cite as

Adaptive Spatial Partitioning for Multidimensional Data Streams

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3341))

Abstract

We propose a space-efficient scheme for summarizing multidimensional data streams. Our scheme can be used for several geometric queries, including natural spatial generalizations of well-studied single-dimensional queries such as icebergs and quantiles.

Research by the last three authors was partially supported by National Science Foundation grants CCR-0049093 and IIS-0121562.

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Author information

Authors and Affiliations

  1. Mentor Graphics Corp., 8005 SW Boeckman Road, Wilsonville, OR, 97070, USA

    John Hershberger

  2. (by courtesy) Computer Science Dept., University of California, Santa Barbara

    John Hershberger

  3. Computer Science Dept., University of California, Santa Barbara, CA, 93106, USA

    Nisheeth Shrivastava, Subhash Suri & Csaba D. Tóth

Authors
  1. John Hershberger
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  2. Nisheeth Shrivastava
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  3. Subhash Suri
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  4. Csaba D. Tóth
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Fudan University, 200433, Shanghai, China

    Rudolf Fleischer

  2. Department of Computer Science, The Hong Kong University of Science and Technology, Hong Kong

    Gerhard Trippen

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© 2004 Springer-Verlag Berlin Heidelberg

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Hershberger, J., Shrivastava, N., Suri, S., Tóth, C.D. (2004). Adaptive Spatial Partitioning for Multidimensional Data Streams. In: Fleischer, R., Trippen, G. (eds) Algorithms and Computation. ISAAC 2004. Lecture Notes in Computer Science, vol 3341. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30551-4_46

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  • DOI: https://doi.org/10.1007/978-3-540-30551-4_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24131-7

  • Online ISBN: 978-3-540-30551-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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