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.
This book constitutes the refereed proceedings of the 5th International Symposium on Rules, RuleML 2011 - Europe, held in Barcelona, Spain, in July 2011 - collocated with the 22nd International Joint Conference on Artificial Intelligence, IJCAI 2011. It is the first of two RuleML events that take place in 2011. The second RuleML Symposium - RuleML 2011 - America - will be held in Fort Lauderdale, FL, USA, in November 2011. The 18 revised full papers, 8 revised short papers and 3 invited track papers presented together with the abstracts of 2 keynote talks were carefully reviewed and selected from 58 submissions. The papers are organized in the following topical sections: rule-based distributed/multi-agent systems; rules, agents and norms; rule-based event processing and reaction rules; fuzzy rules and uncertainty; rules and the semantic Web; rule learning and extraction; rules and reasoning; and rule-based applications.
This book constitutes the refereed proceedings of the International RuleML Symposium on Rule Interchange and Applications, RuleML 2008, held in Orlando, FL, USA, in October 2008 - collocated with the 11th International Business Rules Forum. The 10 revised full papers and 10 revised short papers presented together with 2 demo papers and the abstracts of 3 keynote lectures were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections on rule engineering, rule-based methodologies and applications in policies, electronic contracts and security, rule representation languages and reasoning engines, rule-based methodologies and applications in distributed and heterogeneous environments, natural-language and graphical rule representation and processing, as well as exemplary contributions to the RuleML-2008 challenge.
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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