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Permuted Scaled Matching

  • Ayelet Butman
  • Noa Lewenstein
  • J. Ian Munro
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8486)

Abstract

Scaled matching and permutation matching are two well known paradigms in the domain of pattern matching. Scaled matching refers to finding an occurrence of a pattern which is enlarged proportionally by some scale k within a larger text. Permutation matching is the problem of finding all substrings within a text where the character statistics of the substring and the pattern are the same. Permutation matching is easy, while scaled matching requires innovative solutions. One interesting setting of applications is the merge of the two. The problem of scaled permuted matching (i.e. first permuting and then scaling) has been addressed and solved optimally. However, it was left as an open problem whether there are efficient algorithms for permuted scaled matching. In this paper we solve the problem efficiently in a deterministic setting and optimally in a randomized setting.

Keywords

Pattern Match String Match Binary Search Tree Deterministic Setting Approximate String Match 
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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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ayelet Butman
    • 1
  • Noa Lewenstein
    • 2
  • J. Ian Munro
    • 3
  1. 1.Department of Computer ScienceHolon Institute of TechnologyIsrael
  2. 2.Department of Computer ScienceNetanya CollegeIsrael
  3. 3.Chertion School of Computer ScienceUniversity of WaterlooCanada

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