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Grammatical Inference : Learning Automata and Grammars - Colin de la Higuera

Grammatical Inference

Learning Automata and Grammars

Hardcover

Published: 1st April 2010
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The problem of inducing, learning or inferring grammars has been studied for decades, but only in recent years has grammatical inference emerged as an independent field with connections to many scientific disciplines, including bio-informatics, computational linguistics and pattern recognition. This book meets the need for a comprehensive and unified summary of the basic techniques and results, suitable for researchers working in these various areas.

In Part I, the objects of use for grammatical inference are studied in detail: strings and their topology, automata and grammars, whether probabilistic or not. Part II carefully explores the main questions in the field: What does learning mean? How can we associate complexity theory with learning? In Part III, the author describes a number of techniques and algorithms that allow us to learn from text, from an informant, or through interaction with the environment. These concern automata, grammars, rewriting systems, pattern languages or transducers.

'The scope of the book, the detail of description, the uniformity of notation and treatment, and the enjoyable style make this book an important addition to the library of any computational linguist interested in language learning from data.' Machine Translation
'... this book raises important questions about learning grammars ...' Computing Reviews
"The book under review is the first textbook in this area, written by one of the renowned leading experts in grammatical inference." Henning Fernau, Mathematical Reviews

Preface
Acknowledgements
Introduction
The data and some applications
The Tools
Basic stringology
Representing languages
Representing distributions over strings with automata and grammars
About combinatorics
What Does Learning a Language Mean?
Identifying languages
Learning from text
Active learning
Learning distributions over strings
Learning Algorithms and Techniques
Text learners
Informed learners
Learning with queries
Artificial intelligence techniques
Learning context-free grammars
Learning probabilistic finite automata
Estimating the probabilities
Learning transducers
A very small conclusion
References
Index
Table of Contents provided by Publisher. All Rights Reserved.

ISBN: 9780521763165
ISBN-10: 0521763169
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 432
Published: 1st April 2010
Publisher: Cambridge University Press
Country of Publication: GB
Dimensions (cm): 25.3 x 18.0  x 2.9
Weight (kg): 0.91