Analytic Pattern Matching
From DNA to Twitter

A unique probabilistic approach to studying pattern matching problems in computer science, telecommunications, molecular biology and more.

Philippe Jacquet (Author), Wojciech Szpankowski (Author)

9780521876087, Cambridge University Press

Hardback, published 30 June 2015

385 pages, 40 b/w illus. 110 exercises
25.3 x 18.1 x 2.6 cm, 0.84 kg

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.

Preface
Acknowledgements
Part I. Analysis: 1. Probabilistic models
2. Exact string matching
3. Constrained exact string matching
4. Generalized string matching
5. Subsequence pattern matching
Part II. Applications: 6. Algorithms and data structures
7. Digital trees
8. Suffix trees and Lempel-Ziv'77
9. Lempel-Ziv'78 compression algorithm
10. String complexity
Bibliography
Index.

Subject Areas: Maths for scientists [PDE], Integral calculus & equations [PBKL], Differential calculus & equations [PBKJ], Discrete mathematics [PBD], Mathematics [PB]