Grammatical Inference
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Grammatical Inference: Algorithms and Applications
Author: Alexander Clark
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-09-11
This book constitutes the refereed proceedings of the 9th International Colloquium on Grammatical Inference, ICGI 2008, held in Saint-Malo, France, in September 2008. The 21 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 36 submissions. The topics of the papers presented vary from theoretical results of learning algorithms to innovative applications of grammatical inference, and from learning several interesting classes of formal grammars to applications to natural language processing.
Grammatical Inference: Theoretical Results and Applications
Author: José Sempere
language: en
Publisher: Springer Science & Business Media
Release Date: 2010-09-03
This book constitutes the refereed proceedings of the 10th International Colloquium on Grammatical Inference, ICGI 2010, held in Valencia, Spain, in September 2010. The 18 revised full papers and 14 revised short papers presented were carefully reviewed and selected from numerous submissions. The topics of the papers presented vary from theoretical results about the learning of different formal language classes (regular, context-free, context-sensitive, etc.) to application papers on bioinformatics, language modelling or software engineering. Furthermore there are two invited papers on the topics grammatical inference and games and molecules, languages, and automata.
Grammatical Inference
Author: Colin de la Higuera
language: en
Publisher: Cambridge University Press
Release Date: 2010-04-01
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.