Associative Networks - 1st Edition - ISBN: 9780122563805, 9781483263014

Associative Networks

1st Edition

Representation and Use of Knowledge by Computers

Editors: Nicholas V. Findler
eBook ISBN: 9781483263014
Imprint: Academic Press
Published Date: 28th May 1979
Page Count: 480
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Description

Associative Networks: Representation and Use of Knowledge by Computers is a collection of papers that deals with knowledge base of programs exhibiting some operational aspects of understanding. One paper reviews network formalism that utilizes unobstructed semantics, independent of the domain to which it is applied, that is also capable of handling significant epistemological relationships of concept structuring, attribute/value inheritance, multiple descriptions. Another paper explains network notations that encode taxonomic information; general statements involving quantification; information about processes and procedures; the delineation of local contexts, as well as the relationships between syntactic units and their interpretations. One paper shows that networks can be designed to be intuitively and formally interpretable. Network formalisms are computer-oriented logics which become distinctly significant when access paths from concepts to propositions are built into them. One feature of a topical network organization is its potential for learning. If one topic is too large, it could be broken down where groupings of propositions under the split topics are then based on "co-usage" statistics. As an example, one paper cites the University of Maryland artificial intelligence (AI) group which investigates the control and interaction of a meaning-based parser. The group also analyzes the inferences and predictions from a number of levels based on mundane inferences of actions and causes that can be used in AI. The collection can be useful for computer engineers, computer programmers, mathematicians, and researchers who are working on artificial intelligence.

Table of Contents


List of Contributors

Foreword

Preface

Part I Overview and General Systems

On the Epistemological Status of Semantic Networks

Introduction

1. A Look at the Evolution of Semantic Networks

2. "One Man's Ceiling Is Another Man's Floor"

3. An Epistemologically Explicit Representation

Conclusions

References

Encoding Knowledge in Partitioned Networks

I. Introduction

II. Background and Motivation

III. Basic Network Notions

IV. Partitioning

V. Structures for Logical Deduction

VI. Inheriting Information

VII. Structures for Judgmental Reasoning

VIII. Structures for Reasoning About Processes

IX. Structures for Natural Language Understanding

X. Linearized Net Notation

XI. Implementation

XII. Conclusion

References

A Procedural Semantics for Semantic Networks

1. Introduction

2. Components

3. Organization

4. Metaclasses

5. Inheritance

6. Programs

7. Conclusions

References

The Structure and Organization of a Semantic Net for Comprehension and Inference

1. Introduction

2. A Comprehensive Network Formalism

3. Network Form and Content

4. Organizing Propositions for Inference

5. Implementations

6. Concluding Discussion

References

Part II Theoretically Oriented Efforts

The SNePS Semantic Network Processing System

1. Introduction

2. Basic Representation

3. Inference

4. Parsing and Generating

5. An Example Application—Clue

6. Summary

References

A Predicate Calculus Based Semantic Network for Deductive Searching

1. Introduction

2. Semantic Categories

3. The Representation of Semantics—The Semantic Network

4. Semantic Unification

5. An Illustrative Example

6. Related Work in Semantic Networks

7. Summary

References

Making Preferences More Active

Introduction

1. A Brief Recap of the Processes of the Preference Semantics System

2. Preference-Breaking Already Accommodated in the System

3. Pseudotexts: A Simple Projection System

4. Some Control Issues

5. An Environment for Implementing These Suggestions

6. Relation to Other Systems

7. Discussion

References

Extensional Semantic Networks: Their Representation, Application, and Generation

Introduction

1. Concepts and Relations

2. Extensional Semantic Networks

3. Applicability of ESNs

4. Automatic Generation of Semantic Networks

5. Conclusion

References

Part III Areas of Application

A Heuristic Information Retrieval System Based on Associative Networks

1. Introduction

2. On Some Preliminary Work

3. Design Principles of IRUHS-1

4. System Description

5. Overview and Final Comments

Appendix

References

Re: The Gettysburg Address Representing Social and Political Acts

1. Introduction

2. Triangles

3. Social ACTs

4. Progress: Static Descriptions

5. Relationships Between Authorities and Their Constituents

6. The Gettysburg Address

7. The Use of Triangles

8. Conclusion

Appendix—Conceptual Dependency Notation

References

Rule Forms for Verse, Sentences, and Story Trees

1. Introduction

2. POGEN for Sense and Nonsense

3. From Sentence to Network to Sentence

4. Story Trees

5. Computational Aspects of Semantic Networks and Story Trees

6. Some Rules for Story Trees

7. An Interpreter for Story Grammars

8. Discussion and Conclusions

References

On Representing Commonsense Knowledge

Introduction

I. What Is Commonsense Knowledge?

II. What Is Representing Knowledge?

III. Design Features of Commonsense Representations

IV. Partial Order

V. Route Description

VI. Conclusion

References

Representations to Aid Distributed Understanding in a Multiprogram System

1. Background

2. The Yale Artificial Intelligence Project

3. Choosing Responses

4. Distributed Understanding

5. Processing Notes

6. Discussion

7. Conclusion

References

Five Aspects of a Full-Scale Story Comprehension Model

1. Introduction

2. Parsing: A New Model

3. Meaning Representation of Language and Inference

4. Reference

5. Inference and Inference Conditioning

6. Predictions and Pattern Matching

7. Summary and Conclusion

References

Details

No. of pages:
480
Language:
English
Copyright:
© Academic Press 1979
Published:
Imprint:
Academic Press
eBook ISBN:
9781483263014

About the Editor

Nicholas V. Findler