Handbook Of Exact String Matching Algorithms

String matching is a very important subject in the wider domain of text processing. It consists of finding one, or more generally, all the occurrences of a string (more generally called a pattern) in a text. The Handbook of Exact String Matching Algorithms presents 38 methods for solving this problem. For each, it gives the main features, a description, its C code, an example and references.

String searching is a subject of both theoretical and practical interest in computer science. This book presents a bibliographic overview of the field and an anthology of detailed descriptions of the principal algorithms available. The aim is twofold: on the one hand, to provide an easy-to-read comparison of the available techniques in each area, and on the other, to furnish the reader with a reference to in-depth descriptions of the major algorithms. Topics covered include methods for finding exact and approximate string matches, calculating ‘edit’ distances between strings, finding common sequences and finding the longest repetitions within strings. For clarity, all the algorithms are presented in a uniform format and notation.

Presents recently developed algorithms for searching for simple, multiple and extended strings, regular expressions, exact and approximate matches.

The ability of parallel computing to process large data sets and handle time-consuming operations has resulted in unprecedented advances in biological and scientific computing, modeling, and simulations. Exploring these recent developments, the Handbook of Parallel Computing: Models, Algorithms, and Applications provides comprehensive coverage on a

The book is a collection of peer-reviewed best selected research papers presented at the International Conference on Data Intelligence and Cognitive Informatics (ICDICI 2021), organized by SCAD College of Engineering and Technology, Tirunelveli, India, during July 16–17, 2021. This book discusses new cognitive informatics tools, algorithms, and methods that mimic the mechanisms of the human brain which leads to an impending revolution in understating a large amount of data generated by various smart applications. The book includes novel work in data intelligence domain which combines with the increasing efforts of artificial intelligence, machine learning, deep learning, and cognitive science to study and develop a deeper understanding of the information processing systems.

Abstract: "Experimental comparison of the running time of approximate string matching algorithms for the k differences problem is presented. Given a pattern string, a text string and an integer k, the task is to find all approximate occurrences of the pattern in the text with at most k differences (insertions, deletions, changes). Besides a new algorithm based on suffix automata, we consider six other algorithms based on different approaches including dynamic programming, Boyer-Moore string matching and the distribution of characters. It turns out that none of the algorithms is the best for all values of the problem parameters, and the speed differences between the methods can be large."

Issues of matching and searching on elementary discrete structures arise pervasively in computer science and many of its applications, and their relevance is expected to grow as information is amassed and shared at an accelerating pace. Several algorithms were discovered as a result of these needs, which in turn created the subfield of Pattern Matching. This book provides an overview of the current state of Pattern Matching as seen by specialists who have devoted years of study to the field. It covers most of the basic principles and presents material advanced enough to faithfully portray the current frontier of research. Because of these recent advances, this is the right time for a book that brings together information relevant to both graduate students and specialists in need of an in-depth reference.

Introduces the basic concepts and characteristics of string pattern matching strategies and provides numerous references for further reading. The text describes and evaluates the BF, KMP, BM, and KR algorithms, discusses improvements for string pattern matching machines, and details a technique for detecting and removing the redundant operation of the AC machine. Also explored are typical problems in approximate string matching. In addition, the reader will find a description for applying string pattern matching algorithms to multidimensional matching problems, an investigation of numerous hardware-based solutions for pattern matching, and an examination of hardware approaches for full text search.