Knowledge Base Systems are an integration of conventional database systems with Artificial Intelligence techniques. They provide inference capabilities to the database system by encapsulating the knowledge of the application domain within the database.
Knowledge is the most valuable of all corporate resources that must be captured, stored, re-used and continuously improved, in much the same way as database systems were important in the previous decade.
Flexible, extensible, and yet efficient Knowledge Base Systems are needed to capture the increasing demand for knowledge-based applications which will become a significant market in the next decade.
Knowledge can be expressed in many static and dynamic forms; the most prominent being domain objects, their relationships, and their rules of evolution and transformation. It is important to express and seamlessly use all types of knowledge in a single Knowledge Base System.
Parallel, Object-Oriented, and Active Knowledge Base Systems presents in detail features that a Knowledge Base System should have in order to fulfill the above requirements.
Parallel, Object-Oriented, and Active Knowledge Base Systems covers in detail the following topics: Integration of deductive, production, and active rules in sequential database systems. Integration and inter-operation of multiple rule types into the same Knowledge Base System. Parallel rule matching and execution, for deductive, production, and active rules, in parallel Export, Knowledge Base, and Database Systems. In-depth description of a Parallel, Object-Oriented, and Active Knowledge Base System that integrates all rule paradigms into a single database system without hindering performance.
Parallel, Object-Oriented, and Active Knowledge Base Systems is intended as a graduate-level text for a course on Knowledge Base Systems and as a reference for researchers and practitioners in the areas of database systems, knowledge base systems and Artificial Intelligence.
Explains knowledge base systems as an integration of conventional database systems with artificial intelligence techniques to provide inference capabilities to the database system by encapsulating the knowledge of the application domain within the database and to enable to sharing, ease of maintenance, and reusability of this knowledge, which is usually expressed in the form of high-level, declarative rules such as production and deductive rules. Discusses the various attempts to integrate one or more rule types into databases to provide inference capabilities; and related research issues such as parallel relational and object-oriented database systems. Then presents a complete system based on integrating a parallel object-oriented database model with the multiple-rule integration scheme first described and implemented on a hierarchical multiprocessor architecture. Annotation c. by Book News, Inc., Portland, Or.
List of Figures/Tables. Foreword. Preface. 1. Introduction. Part I: Knowledge Base Systems. 2. Deductive and Active Databases. 3. Integration of Multiple Rule Types. 4. An Active Object-Oriented Knowledge Base System. Part II: Parallel Database and Knowledge Base Systems. 5. Parallel Database Systems. 6. Parallel Knowledge Base Systems. 7. A Parallel Object-Oriented Knowledge Base System. 8. Conclusions and Future Directions. Appendix. References. Index.
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Overview
Knowledge Base Systems are an integration of conventional database systems with Artificial Intelligence techniques. They provide inference capabilities to the database system by encapsulating the knowledge of the application domain within the database.
Knowledge is the most valuable of all corporate resources that must be captured, stored, re-used and continuously improved, in much the same way as database systems were important in the previous decade.
Flexible, extensible, and yet efficient Knowledge Base Systems are needed to capture the increasing demand for knowledge-based applications which will become a significant market in the next decade.
Knowledge can be expressed in many static and dynamic forms; the most prominent being domain objects, their relationships, and their rules of evolution and transformation. It is important to express and seamlessly use all types of knowledge in a single Knowledge Base System.
Parallel, Object-Oriented, and Active Knowledge Base Systems presents in detail features that a Knowledge Base System should have in order to fulfill the above requirements.
Parallel, Object-Oriented, and Active Knowledge Base Systems covers in detail the following topics: Integration of deductive, production, and active rules in sequential database systems. Integration and inter-operation of multiple rule types into the same Knowledge Base System. Parallel rule matching and execution, for deductive, production, and active rules, in parallel Export, Knowledge Base, and Database Systems. In-depth description of a Parallel, Object-Oriented, and Active Knowledge Base System that integrates all rule paradigms into a single database system without hindering performance.
Parallel, Object-Oriented, and Active Knowledge Base Systems is intended as a graduate-level text for a course on Knowledge Base Systems and as a reference for researchers and practitioners in the areas of database systems, knowledge base systems and Artificial Intelligence.
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Explains knowledge base systems as an integration of conventional database systems with artificial intelligence techniques to provide inference capabilities to the database system by encapsulating the knowledge of the application domain within the database and to enable to sharing, ease of maintenance, and reusability of this knowledge, which is usually expressed in the form of high-level, declarative rules such as production and deductive rules. Discusses the various attempts to integrate one or more rule types into databases to provide inference capabilities; and related research issues such as parallel relational and object-oriented database systems. Then presents a complete system based on integrating a parallel object-oriented database model with the multiple-rule integration scheme first described and implemented on a hierarchical multiprocessor architecture. Annotation c. by Book News, Inc., Portland, Or.Product Details
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Table of Contents
List of Figures/Tables. Foreword. Preface. 1. Introduction. Part I: Knowledge Base Systems. 2. Deductive and Active Databases. 3. Integration of Multiple Rule Types. 4. An Active Object-Oriented Knowledge Base System. Part II: Parallel Database and Knowledge Base Systems. 5. Parallel Database Systems. 6. Parallel Knowledge Base Systems. 7. A Parallel Object-Oriented Knowledge Base System. 8. Conclusions and Future Directions. Appendix. References. Index.