Book anouncement
Larry Bookman
lbookman at tiac.net
Fri Oct 21 01:05:43 EDT 1994
*** Announcing a new book ***
available from Kluwer Academic Publishers:
Trajectories Through Knowledge Space: A Dynamic Framework For
Machine Comprehension
by Lawrence A. Bookman
ISBN 0-7923-9487-9
(Order information is in the end of this message)
A central focus of the book is on the developemnt of a framework for
comprehension
connecting research themes from cognitive psychology, cognitive science,
corpus linguistics, and artificial intelligence. The book proposes a new
architecture for semantic memory, providing a framework for addressing the
problem of how to represent background knowledge in a machine.
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Excerpt from FOREWORD
.. this volume is without question a milestone in
language processing scholarship. Bookman has pulled many research threads from
a number of fields to weave a remarkably cohesive picture of the processes
underlying human language comprehension. The net effect is both exciting and
inspiring --- this book will be embraced by studious newcomers and appreciated
by seasoned researchers as well. It is difficult to find cognitive researchers
who have a visionary sense of the big picture. Larry Bookman's vision is both
comprehensive and sparkling in its clarity. Read this book from cover to cover
and then read it again. This is what the field of natural language processing
is all about.
Wendy Lehnert
Professor of Computer Science
Director of the Natural Language Processing Laboratory
University of Massachusetts at Amherst
--------------------------------------------
TABLE OF CONTENTS
List Of Figures
List Of Tables
Foreword By Wendy Lehnert
Preface
Chapter 1 Introduction
1.1 Motivation
1.2 A View of Text Comprehension
1.3 Overview of the LeMICON System
1.4 Implementation
1.5 Points of Interest
1.6 The Impact of this Work on Four Related Fields
1.7 Development of the Two-Tier Model
1.8 A Guide to the Reader
Chapter 2 An Overview of Connectionist and Probabilistic Approaches to
Language Processing
2.1 A Computational Linguistics Perspective
2.2 A Connectionist Perspective
2.3 A Comparison of Connectionist and Probabilistic NLP Methods
2.4 Bridging the Gap --- Integrating Connectionist and Computational
Linguistic Approaches
Chapter 3 Memory Architecture
3.1 The Relational Tier
3.2 The Associational or ASF Tier
3.3 Connecting the Two Tiers
3.4 Working Memory
3.5 How New Knowledge Is Integrated
Chapter 4 The Basic Computation
4.1 A Functional Description of the Algorithm
4.2 Representing the Input
4.3 Computational Details and Program Output at each Step
4.4 General Discussion of the Algorithm
4.5 How LeMICON Handles Binding
4.6 The Links to Psychology and Neurophysiology Revisited
4.7 Some Comparisons to Other Text Understanding Systems
Chapter 5 Analysis of the Interpretation at the Relational and ASF Level
5.1 Introduction
5.2 Analyzing the Interpretation at the Relational Level
5.3 Analyzing the Interpretation at the ASF Level
5.4 Analyzing Time-Dependent Interactions at the ASF Level
5.5 Comparing Interpretations --- A Quantitative Analysis
5.6 An Ablation Study
Chapter 6 Reasoning from the Relational Level of the Representation
6.1 Introduction
6.2 Identifying the Conceptual Roots
6.3 Explaining the Connections Between Events
6.4 Determining Important Concepts in the Interpretation Graph
6.5 Conceptual Roots and their Role in Summarization
Chapter 7 Experiments in Acquiring Knowledge from On-line Corpora
7.1 Introduction
7.2 The Automatic Acquisition of Knowledge from On-line Sources
7.3 The Automatic Construction of the Relational Tier
7.4 The Automatic Construction of the Associational Tier
7.5 How Semantic Memory Evolves in Response to New Input
7.6 Changing the Link Weights
7.7 Implementation Details
Chapter 8 An Analysis of the Acquired Knowledge
8.1 An Alternative View of the UnderlyingKnowledge Representation
8.2 Discussion of Soundness of Approach
8.3 An Evaluation of LeMICON's Representation
8.4 Previous Text Systems Revisited
8.5 The Knowledge Acquisition Continuum
Chapter 9 Conclusions
9.1 Some Consequences of the Two-Tier Model of Memory
9.2 Associational Representations
9.3 The Universality of ASFs
9.4 Scalability
9.5 Automatic Acquisition of Knowledge
9.6 Building Large-Scale Knowledge Bases
9.7 A Link to Corpus Linguistics
9.8 The Interplay between Computation and Representation
9.9 Limitations
Chapter 10 Future Directions
10.1 Expanding The Knowledge Base
10.2 Finding Deeper Semantic Relationships via Corpus Analysis
10.3 Handling Contradictory Input
10.4 Learning New Relationships
10.5 A Basic Level Semantic Encoding
10.6 Child Versus Adult Comprehension
Appendix A The ASFs Used in the LeMICON Experiments
Appendix B A Formal Analysis of the Dynamics
B.1 The Defining Set of Equations
B.2 An Analysis of the Defining Equations
B.3 The ASF Contribution
Appendix C Sample Parsed Input to LeMICON
Appendix D Additional Results with SSS
D.1 Further Examples of Summarization
D.2 Importance
Appendix E Proof of the Boundedness of the Measure I
Appendix F The Dictionary Trees that Describe the Class ``Space''
References
Author Index
Subject Index
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ISBN 0-7923-9487-9
e-mail: Kluwer at world.std.com
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