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Graph Compression by BFS

Approximate String Matching with Compressed Indexes

INESC-ID, R. Alves Redol 9, 1000 Lisboa, Portugal
Department of Computer Science, University of Chile, Avenida Blanco Encalada, 2120, 837-0459 Santiago, Chile Santiago, Chile
CITI, Departamento de Inform´atica, Faculdade de Ciˆencias e Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal
Instituto Superior T´ecnico, Universidade T´ecnica de Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisboa, Portugal
Author to whom correspondence should be addressed.
Algorithms 2009, 2(3), 1105-1136;
Received: 9 July 2009 / Revised: 8 September 2009 / Accepted: 9 September 2009 / Published: 10 September 2009
(This article belongs to the Special Issue Data Compression)
A compressed full-text self-index for a text T is a data structure requiring reduced space and able to search for patterns P in T. It can also reproduce any substring of T, thus actually replacing T. Despite the recent explosion of interest on compressed indexes, there has not been much progress on functionalities beyond the basic exact search. In this paper we focus on indexed approximate string matching (ASM), which is of great interest, say, in bioinformatics. We study ASM algorithms for Lempel-Ziv compressed indexes and for compressed suffix trees/arrays. Most compressed self-indexes belong to one of these classes. We start by adapting the classical method of partitioning into exact search to self-indexes, and optimize it over a representative of either class of self-index. Then, we show that a Lempel- Ziv index can be seen as an extension of the classical q-samples index. We give new insights on this type of index, which can be of independent interest, and then apply them to a Lempel- Ziv index. Finally, we improve hierarchical verification, a successful technique for sequential searching, so as to extend the matches of pattern pieces to the left or right. Most compressed suffix trees/arrays support the required bidirectionality, thus enabling the implementation of the improved technique. In turn, the improved verification largely reduces the accesses to the text, which are expensive in self-indexes. We show experimentally that our algorithms are competitive and provide useful space-time tradeoffs compared to classical indexes. View Full-Text
Keywords: compressed index; approximate string matching; Lempel-Ziv; compressed suffix tree; compressed suffix array compressed index; approximate string matching; Lempel-Ziv; compressed suffix tree; compressed suffix array
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MDPI and ACS Style

Russo, L.M.S.; Navarro, G.; Oliveira, A.L.; Morales, P. Approximate String Matching with Compressed Indexes. Algorithms 2009, 2, 1105-1136.

AMA Style

Russo LMS, Navarro G, Oliveira AL, Morales P. Approximate String Matching with Compressed Indexes. Algorithms. 2009; 2(3):1105-1136.

Chicago/Turabian Style

Russo, Luís M. S., Gonzalo Navarro, Arlindo L. Oliveira, and Pedro Morales. 2009. "Approximate String Matching with Compressed Indexes" Algorithms 2, no. 3: 1105-1136.

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