on searching and extracting strings from compressed textual data /
First Statement of Responsibility
Rossano Venturini
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource (xiv, 120 pages) :
Other Physical Details
illustrations
SERIES
Series Title
Atlantis Studies in Computing,
Volume Designation
volume 4
ISSN of Series
2212-8557 ;
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references
CONTENTS NOTE
Text of Note
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
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SUMMARY OR ABSTRACT
Text of Note
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