Associative Networks

Associative Networks

Representation and Use of Knowledge by Computers

1st Edition - May 28, 1979

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  • Editor: Nicholas V. Findler
  • eBook ISBN: 9781483263014

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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

Product details

  • No. of pages: 480
  • Language: English
  • Copyright: © Academic Press 1979
  • Published: May 28, 1979
  • Imprint: Academic Press
  • eBook ISBN: 9781483263014

About the Editor

Nicholas V. Findler

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