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ASC: COMPRESSED DATA STRUCTURES FOR STRINGS

Information Technology

Computing & Information Technology

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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.

Compressed Data Structures for Strings

POST SECONDARY FOUR YEAR

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Duration

Duration Unit Of Measure

Transaction Type

Front Cover.
Other Frontmatter.
Other Frontmatter.
Title Page.
Copyright Page.
Foreword.
Preface.
Contents.
1: Introduction.
2: Basic Concepts.
3: Optimally Partitioning a Text to Improve Its Compression.
4: Bit-Complexity of Lempel-Ziv Compression.
5: Fast Random Access on Compressed Data.
6: Experiments on Compressed Full-Text Indeexing.
7: Dictionary Indexes.
8: Future Directions of Research.
Bibliography.

Compressed Data Structures for Strings.css-1p8rvzy{position:absolute;padding-left:8px;}

Compressed Data Structures for Strings