Book Description:
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. It is a 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; and hardware architectures for the BWT. This book explores non-traditional applications of the BWT in areas such as: bioinformatics joint source-channel coding; modern information retrieval; machine translation; and test data compression for systems-on-chip. It includes teaching materials ideal for classroom use on courses in: Data Compression and Source Coding; Modern Information Retrieval; Information Science; and Digital Libraries.
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