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Efficient Algorithms for String-Based Negative Selection

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 5666)

Abstract

String-based negative selection is an immune-inspired classification scheme: Given a self-set S of strings, generate a set D of detectors that do not match any element of S. Then, use these detectors to partition a monitor set M into self and non-self elements. Implementations of this scheme are often impractical because they need exponential time in the size of S to construct D. Here, we consider r-chunk and r-contiguous detectors, two common implementations that suffer from this problem, and show that compressed representations of D are constructible in polynomial time for any given S and r. Since these representations can themselves be used to classify the elements in M, the worst-case running time of r-chunk and r-contiguous detector based negative selection is reduced from exponential to polynomial.

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© 2009 Springer-Verlag Berlin Heidelberg

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Elberfeld, M., Textor, J. (2009). Efficient Algorithms for String-Based Negative Selection. In: Andrews, P.S., et al. Artificial Immune Systems. ICARIS 2009. Lecture Notes in Computer Science, vol 5666. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03246-2_14

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  • DOI: https://doi.org/10.1007/978-3-642-03246-2_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03245-5

  • Online ISBN: 978-3-642-03246-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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