Faster subsequence and don't-care pattern matching on compressed texts

Takanori Yamamoto, Hideo Bannai, Shunsuke Inenaga, Masayuki Takeda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Citations (Scopus)

Abstract

Subsequence pattern matching problems on compressed text were first considered by Cégielski et al. (Window Subsequence Problems for Compressed Texts, Proc. CSR 2006, LNCS 3967, pp. 127-136), where the principal problem is: given a string T represented as a straight line program (SLP) of size n, a string P of size m, compute the number of minimal subsequence occurrences of P in T. We present an O(nm) time algorithm for solving all variations of the problem introduced by Cégielski et al.. This improves the previous best known algorithm of Tiskin (Towards approximate matching in compressed strings: Local subsequence recognition, Proc. CSR 2011), which runs in O(nmlogm) time. We further show that our algorithms can be modified to solve a wider range of problems in the same O(nm) time complexity, and present the first matching algorithms for patterns containing VLDC (variable length don't care) symbols, as well as for patterns containing FLDC (fixed length don't care) symbols, on SLP compressed texts.

Original languageEnglish
Title of host publicationCombinatorial Pattern Matching - 22nd Annual Symposium, CPM 2011, Proceedings
Pages309-322
Number of pages14
DOIs
Publication statusPublished - 2011
Event22nd Annual Symposium on Combinatorial Pattern Matching, CPM 2011 - Palermo, Italy
Duration: Jun 27 2011Jun 29 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6661 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other22nd Annual Symposium on Combinatorial Pattern Matching, CPM 2011
Country/TerritoryItaly
CityPalermo
Period6/27/116/29/11

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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