Treffer: Window subsequence problems for compressed texts

Title:
Window subsequence problems for compressed texts
Source:
Computer science (theory and applications)0CSR 2006. :127-136
Publisher Information:
Berlin: Springer, 2006.
Publication Year:
2006
Physical Description:
print, 1 p 1
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
LACL, UMR-FRE 2673, Université Paris 12, Route forestière Hurtault, 77300 Fontainebleau, France
LIAFA, UMR 7089 and Université Paris 6, 2 Place Jussieu, 75254 Paris, France
Steklo, Institute of Mathematics, Fontanka 27, St. Petersburg, Russian Federation
ISSN:
0302-9743
Rights:
Copyright 2007 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.19150241
Database:
PASCAL Archive

Weitere Informationen

Given two strings (a text t of length n and a pattern p) and a natural number w, window subsequence problems consist in deciding whether p occurs as a subsequence of t and/or finding the number of size (at most) w windows of text t which contain pattern p as a subsequence, i.e. the letters of pattern p occur in the text window, in the same order as in p, but not necessarily consecutively (they may be interleaved with other letters). We are searching for subsequences in a text which is compressed using Lempel-Ziv-like compression algorithms, without decompressing the text, and we would like our algorithms to be almost optimal, in the sense that they run in time O(m) where m is the size of the compressed text. The pattern is uncompressed (because the compression algorithms are evolutive: various occurrences of a same pattern look different in the text).