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Lossy Dictionaries

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Algorithms — ESA 2001 (ESA 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2161))

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Abstract

Bloom filtering is an important technique for space efficient storage of a conservative approximation of a set S. The set stored may have up to some specified number of “false positive” members, but all elements of S are included. In this paper we consider lossy dictionaries that are also allowed to have “false negatives”. The aim is to maximize the weight of included keys within a given space constraint. This relaxation allows a very fast and simple data structure making almost optimal use of memory. Being more time efficient than Bloom filters, we believe our data structure to be well suited for replacing Bloom filters in some applications. Also, the fact that our data structure supports information associated to keys paves the way for new uses, as illustrated by an application in lossy image compression.

Partially supported by the IST Programme of the EU under contract number IST-1999-14186 (ALCOM-FT).

Basic Research in Computer Science (http://www.brics.dk), funded by the Danish National Research Foundation.

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Author information

Authors and Affiliations

  1. BRICS Department of Computer Science, University of Aarhus, Denmark

    Rasmus Pagh & Flemming Friche Rodler

Authors
  1. Rasmus Pagh
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  2. Flemming Friche Rodler
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Science and Heinz Nixdorf Institute, Paderborn University, 33095, Paderborn, Germany

    Friedhelm Meyer auf der Heide

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© 2001 Springer-Verlag Berlin Heidelberg

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Pagh, R., Rodler, F.F. (2001). Lossy Dictionaries. In: auf der Heide, F.M. (eds) Algorithms — ESA 2001. ESA 2001. Lecture Notes in Computer Science, vol 2161. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44676-1_25

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  • DOI: https://doi.org/10.1007/3-540-44676-1_25

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42493-2

  • Online ISBN: 978-3-540-44676-7

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