Natural Language Processing and Knowledge Representation

Language for Knowledge and Knowledge for Language

By: Lucja Iwanska

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Paperback | 19 June 2000

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482 Pages

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The essays in this interdisciplinary book cover a range of implementations and designs, from formal computational models to large-scale NL processing systems.

Natural language (NL) refers to human language--complex, irregular, diverse, with all its philosophical problems of meaning and context. Setting a new direction in AI research, this book explores the development of knowledge representation and reasoning (KRR) systems that simulate the role of NL in human information and knowledge processing. Traditionally, KRR systems have incorporated NL as an interface to an expert system or knowledge base that performed tasks separate from NL processing. As this book shows, however, the computational nature of representation and inference in NL makes it the ideal level for all tasks in an intelligent computer system. NL processing combines the qualitative characteristics of human knowledge processing with a computer's quantitative advantages, allowing for in-depth, systematic processing of vast amounts of information. The essays in this interdisciplinary book cover a range of implementations and designs, from formal computational models to large-scale NL processing systems.

Contributors
Syed S. Ali, Bonnie J. Dorr, Karen Ehrlich, Robert Givan, Susan M. Haller, Sanda Harabagiu, Chung Hee Hwang, Lucja Iwanska, Kellyn Kruger, Naveen Mata, David A. McAllester, David D. McDonald, Susan W. McRoy, Dan Moldovan, William J. Rapaport, Lenhart Schubert, Stuart C. Shapiro, Clare R. Voss

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Preface
Contributors
Formal, Computational, Representations and Inference Methods Based on Natural Language
Section Introduction	p. 3
Natural Language Is a Powerful Knowledge Representation System: The UNO Model	p. 7
Natural Language Syntax and First Order Inference	p. 65
Issues in the Representation of Real Texts: The Design of Krisp	p. 77
Episodic Logic Meets Little Red Riding Hood - A Comprehensive Natural Representation for Language Understanding	p. 111
SNePS: A Logic for Natural Language Understanding and Commonsense Reasoning	p. 175
Knowledge Representation and Acquisition for Large-Scale, General-Purpose Natural Language Processing Systems
Section Introduction	p. 193
A Multi-Level Approach to Interlingual Machine Translation: Defining the Interface between Representational Languages	p. 207
Uniform Natural (Language) Spatio-Temporal Logic: Reasoning about Absolute and Relative Space and Time	p. 249
Mixed Depth Representations for Dialog Processing	p. 283
Enriching the WordNet Taxonomy with Contextual Knowledge Acquired from Text	p. 301
Fully Automatic Acquisition of Taxonomic Knowledge from Large Corpora of Texts: Limited-Syntax Knowledge Representation System based on Natural Language	p. 335
A Computational Theory of Vocabulary Acquisition	p. 347
Propositional, First-Order, and Higher-Order Logics	p. 379
Relations, Lattices, Algebras, Generalized Quantifier: Definitions and Theorems	p. 397
Representational and Inferential Challenges of Natural Language: Examples and Data	p. 403
Bibliography	p. 415
Index	p. 441
Table of Contents provided by Blackwell. All Rights Reserved.

Natural Language Processing and Knowledge Representation

Language for Knowledge and Knowledge for Language

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Paperback

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