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The Burrows-Wheeler Transform is one of the best lossless
compression me- ods available. It is an intriguing - even puzzling
- approach to squeezing redundancy out of data, it has an
interesting history, and it has applications well beyond its
original purpose as a compression method. It is a relatively late
addition to the compression canon, and hence our motivation to
write this book, looking at the method in detail, bringing together
the threads that led to its discovery and development, and
speculating on what future ideas might grow out of it. The book is
aimed at a wide audience, ranging from those interested in learning
a little more than the short descriptions of the BWT given in st-
dard texts, through to those whose research is building on what we
know about compression and pattern matching. The ?rst few chapters
are a careful description suitable for readers with an elementary
computer science ba- ground (and these chapters have been used in
undergraduate courses), but later chapters collect a wide range of
detailed developments, some of which are built on advanced concepts
from a range of computer science topics (for example, some of the
advanced material has been used in a graduate c- puter science
course in string algorithms). Some of the later explanations
require some mathematical sophistication, but most should be
accessible to those with a broad background in computer science.
The Burrows-Wheeler Transform is one of the best lossless
compression me- ods available. It is an intriguing - even puzzling
- approach to squeezing redundancy out of data, it has an
interesting history, and it has applications well beyond its
original purpose as a compression method. It is a relatively late
addition to the compression canon, and hence our motivation to
write this book, looking at the method in detail, bringing together
the threads that led to its discovery and development, and
speculating on what future ideas might grow out of it. The book is
aimed at a wide audience, ranging from those interested in learning
a little more than the short descriptions of the BWT given in st-
dard texts, through to those whose research is building on what we
know about compression and pattern matching. The ?rst few chapters
are a careful description suitable for readers with an elementary
computer science ba- ground (and these chapters have been used in
undergraduate courses), but later chapters collect a wide range of
detailed developments, some of which are built on advanced concepts
from a range of computer science topics (for example, some of the
advanced material has been used in a graduate c- puter science
course in string algorithms). Some of the later explanations
require some mathematical sophistication, but most should be
accessible to those with a broad background in computer science.
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