Foundations of Knowledge Base Management: Contributions from Logic, Databases, and Artificial Intelligence Applications

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This book is based on material from current research projects and cooperations and from a recent workshop in the area of Knowledge Base Management Systems. It contains 25 revised papers and related discussions that concentrate on the integration of Database Technology (deductive databases, extended relational technology, object-oriented systems) and Artificial Intelligence (in particular logic programming and knowledge representation). The emphasis of the book is on the integration of DB/AI technology required ...
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Overview

This book is based on material from current research projects and cooperations and from a recent workshop in the area of Knowledge Base Management Systems. It contains 25 revised papers and related discussions that concentrate on the integration of Database Technology (deductive databases, extended relational technology, object-oriented systems) and Artificial Intelligence (in particular logic programming and knowledge representation). The emphasis of the book is on the integration of DB/AI technology required for knowledge Base Management Systems. The book isolates major conceptual contributions, systems extensions, and reseach directions that lead towards that goal. This book is a European counterpart to another volume in the Topics in Information Systems Series, "On Knowledge Base Management Systems", resulting from a North American workshop and edited by M. Brodie and J. Mylopoulos, which concentrates on theoretical results and the more abstract levels of Knowledge Base Management.
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Product Details

  • ISBN-13: 9783540189879
  • Publisher: Springer-Verlag New York, LLC
  • Publication date: 10/28/1989
  • Pages: 579

Table of Contents

Series Description.- Preface.- I. Logic and Knowledge Representation.- 1. The Role of Logic for Data and Knowledge Bases: A Brief Survey.- Discussion.- 2. A Logic-Based Calculus of Events.- Discussion.- 3. Metalanguage and Databases.- Discussion.- 4. Efficient Representation of Incomplete Information About Structured Objects.- 5. Abstraction and Inference Mechanisms for Knowledge Representation.- Discussion.- II. From Data to Facts and Rules.- 6. How To Look at Deductive Databases.- Discussion.- 7. Extending a Relational DBMS Towards a Rule-Based System: An Approach Using Predicate Transition Nets.- 8. Integrated Fact and Rule Management Based on Relational Technology.- 9. Adding a Closure Operator to the Extended Relational Algebra: A Further Step Towards the Integration of Database Techniques and Logic Programming.- Discussion.- III. Architectural Issues in Data and Knowledge Base Integration.- 10. Database Management: A Survey.- Discussion.- 11. Towards Databases for Knowledge Representation.- Discussion.- 12. Large-Scale Knowledge Systems.- 13. Issues in Data Base and Knowledge Base Integration.- Discussion.- 14. Design of a Compiler for a Semantic Data Model.- 15. Two-Mode Evaluation for Dealing with Implicit Interactions Between Logic Programs and Relational Data Bases.- Discussion.- 16. Knowledge Base Management Systems: A Database View.- IV. Knowledge Base Management for AI Applications.- 17. KBMS Requirements of Knowledge-Based Systems.- 18. Conceptual Languages: A Comparison of ADAPLEX, Galileo, and Taxis.- Discussion.- 19. The Software Development Environment as a Knowledge Base Management System.- Discussion.- 20. Retrieving Events from Geometrical Descriptions of Time-Varying Scenes.- 21. A Deductive Solution for Plan Generation.- Discussion.- V. Concluding Remarks.- 22. The Limitations of Logic and Its Role in Artificial Intelligence.- Discussion.- 23. The Need for a Knowledge Representation Framework.- 24. DB Ideas for KBMS.- Comments.- 25. On Application-Oriented and Tool-Oriented Theories.- Discussion.- Final Discussion.- References.- Contributors.
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