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Adaptive Computation of the Swap-Insert Correction Distance

Published: 09 August 2018 Publication History

Abstract

The Swap-Insert Correction distance from a string S of length n to another string L of length mn on the alphabet [1‥σ] is the minimum number of insertions, and swaps of pairs of adjacent symbols, converting S into L. Contrarily to other correction distances, computing it is NP-Hard in the size σ of the alphabet. We describe an algorithm computing this distance in time within O2nmgσ−1), where for each α ∈ [1‥σ] there are nα occurrences of α in S, mα occurrences of α in L, and where g = max α∈[1‥σ] min{nα, mαnα} is a new parameter of the analysis, measuring one aspect of the difficulty of the instance. The difficulty g is bounded by above by various terms, such as the length n of the shortest string S, and by the maximum number of occurrences of a single character in S (maxα ∈[1‥σ] nα). This result illustrates how, in many cases, the correction distance between two strings can be easier to compute than in the worst case scenario.

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Cited By

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  • (2019)Modern Aspects of Complexity Within Formal LanguagesLanguage and Automata Theory and Applications10.1007/978-3-030-13435-8_1(3-30)Online publication date: 14-Feb-2019
  • (2018)Indexed Dynamic Programming to Boost Edit Distance and LCSS ComputationString Processing and Information Retrieval10.1007/978-3-030-00479-8_6(61-73)Online publication date: 14-Sep-2018

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Published In

cover image ACM Transactions on Algorithms
ACM Transactions on Algorithms  Volume 14, Issue 4
October 2018
445 pages
ISSN:1549-6325
EISSN:1549-6333
DOI:10.1145/3266298
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 August 2018
Accepted: 01 May 2018
Revised: 01 May 2018
Received: 01 November 2015
Published in TALG Volume 14, Issue 4

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Author Tags

  1. Adaptive
  2. dynamic programming
  3. edit distance
  4. insert
  5. swap

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  • Refereed

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  • CONICYT FONDECYT/Regular

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Cited By

View all
  • (2019)Modern Aspects of Complexity Within Formal LanguagesLanguage and Automata Theory and Applications10.1007/978-3-030-13435-8_1(3-30)Online publication date: 14-Feb-2019
  • (2018)Indexed Dynamic Programming to Boost Edit Distance and LCSS ComputationString Processing and Information Retrieval10.1007/978-3-030-00479-8_6(61-73)Online publication date: 14-Sep-2018

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