© 1986

On Knowledge Base Management Systems

Integrating Artificial Intelligence and Database Technologies

  • Micheal L. Brodie
  • John Mylopoulos

Part of the Topics in Information Systems book series (TINF)

Table of contents

  1. Front Matter
    Pages i-xxi
  2. Knowledge Base Management Systems

    1. Front Matter
      Pages 1-1
    2. John Mylopoulos
      Pages 3-8
    3. Ron Brachman, Hector Levesque
      Pages 9-12
    4. Hector J. Levesque, Ronald J. Brachman
      Pages 13-34
    5. Frank Manola, Michael L. Brodie
      Pages 35-54
    6. Micheal L. Brodie, John Mylopoulos
      Pages 55-59
  3. Knowledge Bases versus Databases

    1. Front Matter
      Pages 61-61
    2. Hector J. Levesque
      Pages 63-69
    3. David Israel
      Pages 71-75
    4. Gio Wiederhold
      Pages 77-82
    5. Michael L. Brodie, John Mylopoulos
      Pages 83-86
  4. Retrieval/Interface/Reasoning

    1. Front Matter
      Pages 95-95
    2. Matthias Jarke
      Pages 111-119
    3. Jeffrey D. Ullman
      Pages 121-123
    4. Shamin A. Naqvi
      Pages 125-145

About this book


Current experimental systems in industry, government, and the military take advantage of knowledge-based processing. For example, the Defense Advanced Research Projects Agency (DARPA), and the United States Geological Survey (USGS) are supporting the develop­ ment of information systems that contain diverse, vast, and growing repositories of data (e.g., vast databases storing geographic informa­ tion). These systems require powerful reasoning capabilities and pro­ cessing such as data processing, communications, and multidisciplinary of such systems will scientific analysis. The number and importance grow significantly in the near future. Many of these systems are severely limited by current knowledge base and database systems technology. Currently, knowledge-based system technology lacks the means to provide efficient and robust knowledge bases, while database system technology lacks knowledge representation and reasoning capabilities. The time has come to face the complex research problems that must be solved before we can design and implement real, large scale software systems that depend on knowledge-based processing. To date there has been little research directed at integrating knowledge base and database technologies. It is now imperative that such coordinated research be initiated and that it respond to the urgent need for a tech­ nology that will enable operational large-scale knowledge-based system applications.


artificial intelligence conceptual model control database database management information system intelligence knowledge base knowledge representation knowledge-based systems learning memory modeling natural language natural language processing

Editors and affiliations

  • Micheal L. Brodie
    • 1
  • John Mylopoulos
    • 2
  1. 1.Computer Corporation of AmericaCambridgeUSA
  2. 2.Department of Computer ScienceUniversity of TorontoTorontoCanada

Bibliographic information

  • Book Title On Knowledge Base Management Systems
  • Book Subtitle Integrating Artificial Intelligence and Database Technologies
  • Editors Michael L. Brodie
    John Mylopoulos
  • Series Title Topics in Information Systems
  • DOI
  • Copyright Information Springer-Verlag New York 1986
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Hardcover ISBN 978-0-387-96382-2
  • Softcover ISBN 978-1-4612-9383-5
  • eBook ISBN 978-1-4612-4980-1
  • Series ISSN 1431-9365
  • Edition Number 1
  • Number of Pages XXI, 660
  • Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
  • Topics Artificial Intelligence
    Models and Principles
    Information Systems Applications (incl. Internet)
  • Buy this book on publisher's site
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