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Towards approximate matching in compressed strings: Local subsequence recognition. / Tiskin, Alexander.

Computer Science – Theory and Applications (CSR 2011). 2011. стр. 401-414 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 6651).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаяРецензирование

Harvard

Tiskin, A 2011, Towards approximate matching in compressed strings: Local subsequence recognition. в Computer Science – Theory and Applications (CSR 2011). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Том. 6651, стр. 401-414. https://doi.org/10.1007/978-3-642-20712-9_32

APA

Tiskin, A. (2011). Towards approximate matching in compressed strings: Local subsequence recognition. в Computer Science – Theory and Applications (CSR 2011) (стр. 401-414). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 6651). https://doi.org/10.1007/978-3-642-20712-9_32

Vancouver

Tiskin A. Towards approximate matching in compressed strings: Local subsequence recognition. в Computer Science – Theory and Applications (CSR 2011). 2011. стр. 401-414. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-20712-9_32

Author

Tiskin, Alexander. / Towards approximate matching in compressed strings: Local subsequence recognition. Computer Science – Theory and Applications (CSR 2011). 2011. стр. 401-414 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

BibTeX

@inproceedings{963ea726eeb74f52b1ff7801519912e5,
title = "Towards approximate matching in compressed strings: Local subsequence recognition",
abstract = "A grammar-compressed (GC) string is a string generated by a context-free grammar. This compression model includes LZ78 and LZW compression as a special case. We consider the longest common subsequence problem and the local subsequence recognition problem on a GC-text against a plain pattern. We show that, surprisingly, both problems can be solved in time that is within a polylogarithmic factor of the best existing algorithms for the same problems on a plain text. In a wider context presented elsewhere, we use these results as a stepping stone to efficient approximate matching on a GC-text. {\textcopyright} 2011 Springer-Verlag Berlin Heidelberg.",
author = "Alexander Tiskin",
year = "2011",
month = jun,
day = "23",
doi = "10.1007/978-3-642-20712-9_32",
language = "English",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "401--414",
booktitle = "Computer Science – Theory and Applications (CSR 2011)",

}

RIS

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T1 - Towards approximate matching in compressed strings: Local subsequence recognition

AU - Tiskin, Alexander

PY - 2011/6/23

Y1 - 2011/6/23

N2 - A grammar-compressed (GC) string is a string generated by a context-free grammar. This compression model includes LZ78 and LZW compression as a special case. We consider the longest common subsequence problem and the local subsequence recognition problem on a GC-text against a plain pattern. We show that, surprisingly, both problems can be solved in time that is within a polylogarithmic factor of the best existing algorithms for the same problems on a plain text. In a wider context presented elsewhere, we use these results as a stepping stone to efficient approximate matching on a GC-text. © 2011 Springer-Verlag Berlin Heidelberg.

AB - A grammar-compressed (GC) string is a string generated by a context-free grammar. This compression model includes LZ78 and LZW compression as a special case. We consider the longest common subsequence problem and the local subsequence recognition problem on a GC-text against a plain pattern. We show that, surprisingly, both problems can be solved in time that is within a polylogarithmic factor of the best existing algorithms for the same problems on a plain text. In a wider context presented elsewhere, we use these results as a stepping stone to efficient approximate matching on a GC-text. © 2011 Springer-Verlag Berlin Heidelberg.

UR - http://www.scopus.com/inward/record.url?scp=79959299019&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-20712-9_32

DO - 10.1007/978-3-642-20712-9_32

M3 - Conference contribution

AN - SCOPUS:79959299019

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

SP - 401

EP - 414

BT - Computer Science – Theory and Applications (CSR 2011)

ER -

ID: 127758484