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The Information Theory of Perfect Hashing

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Abstract

Fredman and Komlós [1] have used an interesting information-theoretic technique to derive the hitherto sharpest converse (nonexistence) bounds for the problem of perfect hashing. It seems to me that this is the first use of “hard core information theory” in combinatorics.

Keywords

Information Theory Hash Function Random Selection Hungarian Academy Proof Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    M. Fredman and J. Komlós, “On the Size of Separating Systems and Perfect Hash Functions,” SIAM J. Algebraic Discrete Meth., 5, No. 1, pp. 61–68 (1984).zbMATHCrossRefGoogle Scholar
  2. [2]
    J. Kömer, “Fredman-Komlós Bounds and Information Theory, SIAM J. Algebraic Discrete Meth., 7, No. 4, pp. 560–570 (1986).CrossRefGoogle Scholar
  3. [3]
    J. Kömer, “Coding of an Information Source Having Ambiguous Alphabet and the Entropy of Graphs,” Transactions of the 6th Prague Conference on Information Theory, Academia, Prague 1973, pp. 411–425.Google Scholar
  4. [4]
    J. Kömer and K. Marton, “New Bounds for Perfect Hashing via Information Theory,” submitted to Eur. J. Combinatorics.Google Scholar

Copyright information

© Springer-Verlag New York Inc. 1987

Authors and Affiliations

  1. 1.Mathematical Institute of the Hungarian Academy of SciencesBudapestHungary

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