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Knowledge Engineering

Unifying Knowledge Base and Database Design

  • Book
  • © 1998

Overview

Authors:
  1. John Debenham

    1. School of Computing Sciences, University of Technology, Sydney, Australia

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  • A systematic and detailed presentation of a design methodology for knowledge-based systems
  • Data, information, and knowledge are integrated in a unified methodology
  • The methodology builds a maintenance mechanism into the design

Part of the book series: Artificial Intelligence (AI)

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Table of contents (12 chapters)

  1. Front Matter

    Pages I-XIV
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  2. Fundamentals

    • John Debenham
    Pages 1-31

  3. Non-unified design

    • John Debenham
    Pages 33-56

  4. Items

    • John Debenham
    Pages 57-97

  5. Objects

    • John Debenham
    Pages 99-146

  6. Schemas

    • John Debenham
    Pages 147-175

  7. Normalisation

    • John Debenham
    Pages 177-235

  8. Specification

    • John Debenham
    Pages 237-268

  9. Analysis

    • John Debenham
    Pages 269-317

  10. Function

    • John Debenham
    Pages 319-342

  11. Layout

    • John Debenham
    Pages 343-368

  12. Maintenance

    • John Debenham
    Pages 369-390

  13. Case study

    • John Debenham
    Pages 391-448

  14. Back Matter

    Pages 449-467
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Keywords

About this book

This monograph describes a methodology for the design of knowledge-based systems. A knowledge-based system contains knowledge as well as information and data. The information and data in such a system can be modelled and imple­ mented as a database. The knowledge in such a system can be implemented either in a programming language or in an expert systems shell. This methodology has two distinguishing features. First, it is "unified". A unified methodology repre­ sents the data, information and knowledge in a homogeneous manner, as well as the relationships between them. Second, the methodology builds a maintenance mechanism into the design. In knowledge engineering terms, the representation used by this methodology to model knowledge bases applies equally to databases. In database terms, the representation used by this methodology to model databases applies equally to the database rules. The unified methodology unifies the design of the "knowledge base compo­ nent" and the "database component". "Unification" is achieved in five senses.

Authors and Affiliations

  • School of Computing Sciences, University of Technology, Sydney, Australia

    John Debenham

Bibliographic Information

  • Book Title: Knowledge Engineering

  • Book Subtitle: Unifying Knowledge Base and Database Design

  • Authors: John Debenham

  • Series Title: Artificial Intelligence

  • DOI: https://doi.org/10.1007/978-3-642-72034-5

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag Berlin Heidelberg 1998

  • Softcover ISBN: 978-3-642-72036-9Published: 13 December 2011

  • eBook ISBN: 978-3-642-72034-5Published: 06 December 2012

  • Series ISSN: 1431-0066

  • Edition Number: 1

  • Number of Pages: XIV, 466

  • Topics: Artificial Intelligence, Database Management, Software Engineering

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