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E-book

Title Topics in grammatical inference / Jeffrey Heinz, José M. Sempere, editors
Published Berlin : Springer, 2016

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Description 1 online resource (xvii, 247 pages) : illustrations (some color)
Contents Introduction -- Gold-Style Learning Theory -- Efficiency in the Identification in the Limit Learning Paradigm -- Learning Grammars and Automata with Queries -- On the Inference of Finite State Automata from Positive and Negative Data -- Learning Probability Distributions Generated by Finite-State Machines -- Distributional Learning of Context-Free and Multiple -- Context-Free Grammars -- Learning Tree Languages -- Learning the Language of Biological Sequences
Summary 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
Bibliography Includes bibliographical references
Notes Online resource; title from PDF title page (SpringerLink, viewed May 9, 2016)
Subject Machine learning.
Natural language processing (Computer science)
COMPUTERS -- General.
Machine learning
Natural language processing (Computer science)
Form Electronic book
Author Heinz, Jeffrey, 1974- editor.
Sempere, José M., editor.
ISBN 9783662483954
3662483955
3662483939
9783662483930