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Compressed Data Structures for Strings On Searching and Extracting Strings from Compressed Textual Data /
Data compression is mandatory to manage massive datasets, indexing is fundamental to query them. However, their goals appear as counterposed: the former aims at minimizing data redundancies, whereas the latter augments the dataset with auxiliary information to speed up the query resolution. In this...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Paris :
Atlantis Press : Imprint: Atlantis Press,
2014.
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| Edición: | 1st ed. 2014. |
| Colección: | Atlantis Studies in Computing,
4 |
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 001 | 978-94-6239-033-1 | ||
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| 008 | 131031s2014 fr | s |||| 0|eng d | ||
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| 024 | 7 | |a 10.2991/978-94-6239-033-1 |2 doi | |
| 050 | 4 | |a QA76.9.C62 | |
| 072 | 7 | |a UK |2 bicssc | |
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| 072 | 7 | |a UK |2 thema | |
| 082 | 0 | 4 | |a 004.01513 |2 23 |
| 100 | 1 | |a Venturini, Rossano. |e author. |0 (orcid)0000-0002-9830-3936 |1 https://orcid.org/0000-0002-9830-3936 |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Compressed Data Structures for Strings |h [electronic resource] : |b On Searching and Extracting Strings from Compressed Textual Data / |c by Rossano Venturini. |
| 250 | |a 1st ed. 2014. | ||
| 264 | 1 | |a Paris : |b Atlantis Press : |b Imprint: Atlantis Press, |c 2014. | |
| 300 | |a XIV, 118 p. 18 illus. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
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| 490 | 1 | |a Atlantis Studies in Computing, |x 2212-8565 ; |v 4 | |
| 505 | 0 | |a Introduction -- Basic concepts -- Optimally partitioning a text to improve its compression -- Bit-complexity of Lempel-Ziv compression -- Fast random access on compressed data -- Experiments on compressed full-text indexing -- Dictionary indexes -- Future directions of research. | |
| 520 | |a Data compression is mandatory to manage massive datasets, indexing is fundamental to query them. However, their goals appear as counterposed: the former aims at minimizing data redundancies, whereas the latter augments the dataset with auxiliary information to speed up the query resolution. In this monograph we introduce solutions that overcome this dichotomy. We start by presenting the use of optimization techniques to improve the compression of classical data compression algorithms, then we move to the design of compressed data structures providing fast random access or efficient pattern matching queries on the compressed dataset. These theoretical studies are supported by experimental evidences of their impact in practical scenarios. | ||
| 650 | 0 | |a Computer arithmetic and logic units. | |
| 650 | 1 | 4 | |a Arithmetic and Logic Structures. |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9789462390348 |
| 776 | 0 | 8 | |i Printed edition: |z 9789462390324 |
| 830 | 0 | |a Atlantis Studies in Computing, |x 2212-8565 ; |v 4 | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.2991/978-94-6239-033-1 |z Texto Completo |
| 912 | |a ZDB-2-SMA | ||
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| 950 | |a Mathematics and Statistics (SpringerNature-11649) | ||
| 950 | |a Mathematics and Statistics (R0) (SpringerNature-43713) | ||