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Machine-Aided Linguistic Discovery: An Introduction and Some Examples

Autor Vladimir Pericliev
en Limba Engleză Hardback – 28 ian 2010
Solving linguistic problems frequently reduces to carrying out tasks that are computationally complex and therefore requires automation. This book is an introduction to machine-aided linguistic discovery, a novel research area, and argues for the fruitfulness of the computational approach by presenting a basic conceptual apparatus and several intelligent discovery programs. One of the programs models the fundamental Saussurian notion of "system" and thus, almost a century after the introduction of this concept and structuralism in general, linguists are for the first time capable of handling adequately this recurring computationally complex task. Another program models the problem of searching for Greenbergian language universals and is capable of stating its discoveries in an intelligible form, a comprehensive English language text. It is the first computer program to generate a whole scientific article. A third program detects potential inconsistencies in genetic language classifications. These, and the other programs described in this book, are applied with noteworthy results to substantial problems from diverse linguistic disciplines such as structural semantics, phonology, typology and historical linguistics. Machine-Aided Linguistic Discovery will be of interest to linguists and to scholars working in the areas of computational linguistics, Artificial Intelligence and the philosophy of science.
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Specificații

ISBN-13: 9781845536602
ISBN-10: 1845536606
Pagini: 330
Ilustrații: Illustrations
Dimensiuni: 157 x 236 x 25 mm
Greutate: 0.64 kg
Editura: Equinox Publishing (UK)
Locul publicării:United Kingdom

Notă biografică

Vladimir Pericliev is Senior Researcher at the Institute of Mathematics & Informatics, Bulgarian Academy of Sciences, with over 60 publications in general and computational linguistics, Artificial Intelligence and philosophy of science.

Cuprins

Introduction 1. Introducing the Basic Notions 2. Parsimonious Discrimination I: KINSHIP and the Problem of Componential Analysis 3. Parsimonious Discrimination II: MPD and Other Applications 4. Inferring Plausible Laws/Patterns I: UNIVAUTO and the Problem of Language Universals 5. Inferring Plausible Laws/Patterns II: UNIVAUTO and Implicational Phonological Universals 6. Inferring Simplest Laws/Patterns: MINTYP and the Problem of Describing a Typology 7. Detecting Significant Similarities: RECLASS and the Problem of Genetic Language Classification 8. Concluding Remarks