Overview
- Contributing authors among leading researchers in this
- Valuable for researchers and graduate students in theoretical computer science,
- computational linguistics, bioinformatics, and cognitive psychology
- Topics of foundational interest with mature and established results, algorithms and conclusions
- Includes supplementary material: sn.pub/extras
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Table of contents (8 chapters)
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Front Matter
Keywords
About this book
This book explains advanced theoretical and application-related issues in grammatical inference, a research area inside the inductive inference paradigm for machine learning. The first three chapters of the book deal with issues regarding theoretical learning frameworks; the next four chapters focus on the main classes of formal languages according to Chomsky's hierarchy, in particular regular and context-free languages; and the final chapter addresses the processing of biosequences.
The topics chosen are of foundational interest with relatively mature and established results, algorithms and conclusions. The book will be of value to researchers and graduate students in areas such as theoretical computer science, machine learning, computational linguistics, bioinformatics, and cognitive psychology who are engaged with the study of learning, especially of the structure underlying the concept to be learned. Some knowledge of mathematics and theoretical computer science, including formal language theory, automata theory, formal grammars, and algorithmics, is a prerequisite for reading this book.
Editors and Affiliations
Bibliographic Information
Book Title: Topics in Grammatical Inference
Editors: Jeffrey Heinz, José M. Sempere
DOI: https://doi.org/10.1007/978-3-662-48395-4
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2016
Hardcover ISBN: 978-3-662-48393-0Published: 13 May 2016
Softcover ISBN: 978-3-662-56920-7Published: 27 May 2018
eBook ISBN: 978-3-662-48395-4Published: 04 May 2016
Edition Number: 1
Number of Pages: XVII, 247
Number of Illustrations: 49 b/w illustrations, 7 illustrations in colour
Topics: Theory of Computation, Artificial Intelligence, Computational Linguistics, Computational Biology/Bioinformatics