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Encyclopedia of Algorithms pp 1366–1369Cite as

Multidimensional Compressed Pattern Matching

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  • 78 Accesses

Years and Authors of Summarized Original Work

  • 2003; Amir, Landau, Sokol

Problem Definition

Letc be a given compression algorithm, and let c(D) be the result of c compressing data D. The compressed search problem with compression algorithm c is defined as follows.

Input: Compressed~text \( { c(T) } \) and~pattern P.

Output: All locations in T where pattern P occurs.

A compressed matching algorithm is optimal if its time complexity is \( { O(|c(T)|) } \).

Although optimality in terms of time is always important, when dealing with compression, the criterion of extra spaceis perhaps more important (Ziv, Personal communication, 1995). Applications employ compression techniques specifically because there is a limited amount of available space. Thus, it is not sufficient for a compressed matching algorithm to be optimal in terms of time, it must also satisfy the given space constraints. Space constraints may be due to limited amount of disk space (e.g., on a server), or they may be related...

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Recommended Reading

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Author information

Authors and Affiliations

  1. Department of Computer Science, Bar-Ilan University, Ramat-Gan, Israel

    Amihood Amir

  2. Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA

    Amihood Amir

Authors
  1. Amihood Amir
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, USA

    Ming-Yang Kao

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© 2016 Springer Science+Business Media New York

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Amir, A. (2016). Multidimensional Compressed Pattern Matching. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2864-4_246

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