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Modelling Spatial Knowledge on a Linguistic Basis

Theory - Prototype - Integration

  • Book
  • © 1991

Overview

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 481)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

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Table of contents (4 chapters)

Keywords

About this book

On the basis of a semantic analysis of dimension terms, this book develops a theory about knowledge of spatial objects, which is significant for cognitive linguistics and artificial intelligence. This new approach to knowledge structure evolves in a three-step process: - adoption of the linguistic theory with its elements, principles and representational levels, - implementation of the latter in a Prolog prototype, and - integration of the prototype into a large natural language understanding system. The study documents interdisciplinary research at work: the model of spatial knowledge is the fruit of the cooperative efforts of linguists, computational linguists, and knowledge engineers, undertaken in that logical and chronological order. The book offers a two-level approach to semantic interpretation and proves that it works by means of a precise computer implementation, which in turn is applied to support a task-independent knowledge representation system. Each of these stages is described in detail, and the links are made explicit, thus retracing the evolution from theory to practice.

Bibliographic Information

  • Book Title: Modelling Spatial Knowledge on a Linguistic Basis

  • Book Subtitle: Theory - Prototype - Integration

  • Authors: Ewald Lang, Kai-Uwe Carstensen, Geoffrey Simmons

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/BFb0020982

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag Berlin Heidelberg 1991

  • Softcover ISBN: 978-3-540-53718-2Published: 26 February 1991

  • eBook ISBN: 978-3-540-47051-9Published: 23 November 2005

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: IX, 140

  • Topics: Artificial Intelligence

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