Fomichov Vladimir. Semantics-Oriented Natural Language Processing: Mathematical Models and Algorithms

Springer. New York, USA. 2010. 328 pages. Includes glossary, references, and index.This book examines key issues in designing semantics-oriented natural language processing systems. A broad conceptual framework for describing structured meanings of NL-texts is obtained by defining a new class of formal languages called standard knowledge languages (SK-languages) using a system theoretical approach. Readers will gain knowledge of these languages and will learn a way of building semantic representations using them.With extensive use of examples and illustrations to clarify complex material and demonstrate practical applications, generous historical and bibliographical notes, end-of-chapter exercises, and glossaries, this book will serve as an ideal graduate-level textbook, as well as a good reference for researchers and practitioners who deal with the various problems involving semantics of natural language texts.Comprehensive Mathematical Framework for the Development of Semantic Technologies
Mathematical Models for Designing Natural Language Processing Introduction to Integral Formal Semantics of Natural Language
A Mathematical Model for Describing a System of Primary Units of Conceptual Level Used by Applied Intelligent Systems
A Mathematical Model for Describing Structured Meanings of Natural Language Sentences and Discourses
A Study of the Expressive Possibilities of SK-Languages
The Significance of a New Mathematical Model for Web Science, E-science, and E-commerce
Formal Methods and Algorithms for the Design of Semantics-Oriented Linguistic Processors
A Mathematical Model of a Linguistic Database
A New Method of Transforming Texts into Semantic Representations
Algorithm of Building a Matrix Semantic-Syntactic Representation of a Natural Language Text
An Algorithm of Semantic Representation Assembly
Natural Language Processing ApplicationsISBN: 978-0-387-72924-4; e-ISBN: 978-0-387-72926-8; DOI 10.1007/978-0-387-72926-8