A Faster longest common extension algorithm on compressed strings and its applications

(Invited talk)

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

3 Citations (Scopus)

Abstract

In this talk, we introduce our recent data structure for longest common extension (LCE) queries on grammar-compressed strings. Our preprocessing input is a straight-line program (SLP) of size n describing a string w of length N, which is essentially a CFG in the Chomsky normal form generating only w. We can preprocess the input SLP in O(n log log n logN log N) time so that later, given two variables and two positions in the strings derived by the variables, we can answer the corresponding LCE query in O(logN log N) time. Our LCE data structure requires O(z logN log N) words of space, where z is the size of the Lempel-Ziv 77 factorization of w. We also show several applications of our LCE data structure on SLPs.

Original languageEnglish
Title of host publicationProceedings of the Prague Stringology Conference 2015, PSC 2015
EditorsJan Zd'arek, Jan Holub
PublisherPrague Stringology Club
Pages1-4
Number of pages4
ISBN (Electronic)9788001057872
Publication statusPublished - Jan 1 2015
Event19th Prague Stringology Conference, PSC 2015 - Prague, Czech Republic
Duration: Aug 24 2015Aug 26 2015

Publication series

NameProceedings of the Prague Stringology Conference 2015, PSC 2015

Other

Other19th Prague Stringology Conference, PSC 2015
CountryCzech Republic
CityPrague
Period8/24/158/26/15

Fingerprint

Strings
Straight-line Programs
Data Structures
Query
Grammar
Normal Form
Preprocessing
Factorization

All Science Journal Classification (ASJC) codes

  • Mathematics(all)

Cite this

Inenaga, S. (2015). A Faster longest common extension algorithm on compressed strings and its applications: (Invited talk). In J. Zd'arek, & J. Holub (Eds.), Proceedings of the Prague Stringology Conference 2015, PSC 2015 (pp. 1-4). (Proceedings of the Prague Stringology Conference 2015, PSC 2015). Prague Stringology Club.

A Faster longest common extension algorithm on compressed strings and its applications : (Invited talk). / Inenaga, Shunsuke.

Proceedings of the Prague Stringology Conference 2015, PSC 2015. ed. / Jan Zd'arek; Jan Holub. Prague Stringology Club, 2015. p. 1-4 (Proceedings of the Prague Stringology Conference 2015, PSC 2015).

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

Inenaga, S 2015, A Faster longest common extension algorithm on compressed strings and its applications: (Invited talk). in J Zd'arek & J Holub (eds), Proceedings of the Prague Stringology Conference 2015, PSC 2015. Proceedings of the Prague Stringology Conference 2015, PSC 2015, Prague Stringology Club, pp. 1-4, 19th Prague Stringology Conference, PSC 2015, Prague, Czech Republic, 8/24/15.
Inenaga S. A Faster longest common extension algorithm on compressed strings and its applications: (Invited talk). In Zd'arek J, Holub J, editors, Proceedings of the Prague Stringology Conference 2015, PSC 2015. Prague Stringology Club. 2015. p. 1-4. (Proceedings of the Prague Stringology Conference 2015, PSC 2015).
Inenaga, Shunsuke. / A Faster longest common extension algorithm on compressed strings and its applications : (Invited talk). Proceedings of the Prague Stringology Conference 2015, PSC 2015. editor / Jan Zd'arek ; Jan Holub. Prague Stringology Club, 2015. pp. 1-4 (Proceedings of the Prague Stringology Conference 2015, PSC 2015).
@inproceedings{bcf1b3758b2542b4b65c864d299e91d1,
title = "A Faster longest common extension algorithm on compressed strings and its applications: (Invited talk)",
abstract = "In this talk, we introduce our recent data structure for longest common extension (LCE) queries on grammar-compressed strings. Our preprocessing input is a straight-line program (SLP) of size n describing a string w of length N, which is essentially a CFG in the Chomsky normal form generating only w. We can preprocess the input SLP in O(n log log n logN log N) time so that later, given two variables and two positions in the strings derived by the variables, we can answer the corresponding LCE query in O(logN log N) time. Our LCE data structure requires O(z logN log N) words of space, where z is the size of the Lempel-Ziv 77 factorization of w. We also show several applications of our LCE data structure on SLPs.",
author = "Shunsuke Inenaga",
year = "2015",
month = "1",
day = "1",
language = "English",
series = "Proceedings of the Prague Stringology Conference 2015, PSC 2015",
publisher = "Prague Stringology Club",
pages = "1--4",
editor = "Jan Zd'arek and Jan Holub",
booktitle = "Proceedings of the Prague Stringology Conference 2015, PSC 2015",

}

TY - GEN

T1 - A Faster longest common extension algorithm on compressed strings and its applications

T2 - (Invited talk)

AU - Inenaga, Shunsuke

PY - 2015/1/1

Y1 - 2015/1/1

N2 - In this talk, we introduce our recent data structure for longest common extension (LCE) queries on grammar-compressed strings. Our preprocessing input is a straight-line program (SLP) of size n describing a string w of length N, which is essentially a CFG in the Chomsky normal form generating only w. We can preprocess the input SLP in O(n log log n logN log N) time so that later, given two variables and two positions in the strings derived by the variables, we can answer the corresponding LCE query in O(logN log N) time. Our LCE data structure requires O(z logN log N) words of space, where z is the size of the Lempel-Ziv 77 factorization of w. We also show several applications of our LCE data structure on SLPs.

AB - In this talk, we introduce our recent data structure for longest common extension (LCE) queries on grammar-compressed strings. Our preprocessing input is a straight-line program (SLP) of size n describing a string w of length N, which is essentially a CFG in the Chomsky normal form generating only w. We can preprocess the input SLP in O(n log log n logN log N) time so that later, given two variables and two positions in the strings derived by the variables, we can answer the corresponding LCE query in O(logN log N) time. Our LCE data structure requires O(z logN log N) words of space, where z is the size of the Lempel-Ziv 77 factorization of w. We also show several applications of our LCE data structure on SLPs.

UR - http://www.scopus.com/inward/record.url?scp=84978492375&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84978492375&partnerID=8YFLogxK

M3 - Conference contribution

T3 - Proceedings of the Prague Stringology Conference 2015, PSC 2015

SP - 1

EP - 4

BT - Proceedings of the Prague Stringology Conference 2015, PSC 2015

A2 - Zd'arek, Jan

A2 - Holub, Jan

PB - Prague Stringology Club

ER -