### 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 language | English |
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Title of host publication | Combinatorial Pattern Matching - 22nd Annual Symposium, CPM 2011, Proceedings |

Pages | 309-322 |

Number of pages | 14 |

DOIs | |

Publication status | Published - Jul 13 2011 |

Event | 22nd Annual Symposium on Combinatorial Pattern Matching, CPM 2011 - Palermo, Italy Duration: Jun 27 2011 → Jun 29 2011 |

### Publication series

Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 6661 LNCS |

ISSN (Print) | 0302-9743 |

ISSN (Electronic) | 1611-3349 |

### Other

Other | 22nd Annual Symposium on Combinatorial Pattern Matching, CPM 2011 |
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Country | Italy |

City | Palermo |

Period | 6/27/11 → 6/29/11 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Theoretical Computer Science
- Computer Science(all)

### Cite this

*Combinatorial Pattern Matching - 22nd Annual Symposium, CPM 2011, Proceedings*(pp. 309-322). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6661 LNCS). https://doi.org/10.1007/978-3-642-21458-5_27

**Faster subsequence and don't-care pattern matching on compressed texts.** / Yamamoto, Takanori; Bannai, Hideo; Inenaga, Shunsuke; Takeda, Masayuki.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Combinatorial Pattern Matching - 22nd Annual Symposium, CPM 2011, Proceedings.*Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6661 LNCS, pp. 309-322, 22nd Annual Symposium on Combinatorial Pattern Matching, CPM 2011, Palermo, Italy, 6/27/11. https://doi.org/10.1007/978-3-642-21458-5_27

}

TY - GEN

T1 - Faster subsequence and don't-care pattern matching on compressed texts

AU - Yamamoto, Takanori

AU - Bannai, Hideo

AU - Inenaga, Shunsuke

AU - Takeda, Masayuki

PY - 2011/7/13

Y1 - 2011/7/13

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=79960081284&partnerID=8YFLogxK

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U2 - 10.1007/978-3-642-21458-5_27

DO - 10.1007/978-3-642-21458-5_27

M3 - Conference contribution

AN - SCOPUS:79960081284

SN - 9783642214578

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 309

EP - 322

BT - Combinatorial Pattern Matching - 22nd Annual Symposium, CPM 2011, Proceedings

ER -