How do you distinguish a cat from a dog by their DNA? Did
Shakespeare really write all of his plays? Pattern matching
techniques can offer answers to these questions and to many others,
from molecular biology, to telecommunications, to classifying
Twitter content. This book for researchers and graduate students
demonstrates the probabilistic approach to pattern matching, which
predicts the performance of pattern matching algorithms with very
high precision using analytic combinatorics and analytic
information theory. Part I compiles known results of pattern
matching problems via analytic methods. Part II focuses on
applications to various data structures on words, such as digital
trees, suffix trees, string complexity and string-based data
compression. The authors use results and techniques from Part I and
also introduce new methodology such as the Mellin transform and
analytic depoissonization. More than 100 end-of-chapter problems
help the reader to make the link between theory and practice.
General
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