The Burrows-Wheeler Transform is a text transformation scheme that has found applications in different aspects of the data explosion problem, from data compression to index structures and search. The BWT belongs to a new class of compression algorithms, distinguished by its ability to perform compression by sorted contexts. More recently, the BWT has also found various applications in addition to text data compression, such as in lossless and lossy image compression, tree-source identification, bioinformatics, machine translation, shape matching, and test data compression.
This book will serve as a reference for seasoned professionals or researchers in the area, while providing a gentle introduction, making it accessible for senior undergraduate students or first year graduate students embarking upon research in compression, pattern matching, full text retrieval, compressed index structures, or other areas related to the BWT.
Key Features
Comprehensive resource for information related to different aspects of the Burrows-Wheeler Transform including:
Gentle introduction to the BWT
History of the development of the BWT
Detailed theoretical analysis of algorithmic issues and performance limits
Searching on BWT compressed data
Hardware architectures for the BWT
Explores non-traditional applications of the BWT in areas such as:
Bioinformatics
Joint source-channel coding
Modern information retrieval
Machine translation
Test data compression for systems-on-chip
Teaching materials ideal for classroom use on courses in:
Data Compression and Source Coding
Modern Information Retrieval
Information Science
Digital Libraries

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