Toward principles for the design of ontologies used for knowledge sharing
International Journal of Human-Computer Studies - Special issue: the role of formal ontology in the information technology
Developing Knowledge-Based Systems with MIKE
Automated Software Engineering
CommonKADS: A Comprehensive Methodology for KBS Development
IEEE Expert: Intelligent Systems and Their Applications
Some Issues in Design of Distributed Deductive Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Visualizing Semantic Web proofs of defeasible logic in the DR-DEVICE system
Knowledge-Based Systems
Information modelling for sustainable buildings
Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services
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Knowledge engineering is a discipline concerned with constructing and maintaining knowledge bases to store knowledge of various domains and using the knowledge by automated reasoning techniques to solve problems in domains that ordinarily require human logical reasoning. Therefore, the two key issues in knowledge engineering are how to construct and maintain knowledge bases, and how to reason out new knowledge from known knowledge effectively and efficiently. The objective of this paper is the comparison and evaluation of a Deductive Database system (ConceptBase) with a Semantic Web reasoning engine (Racer). For each system a knowledge base is implemented in such a way that a fair comparison can be achieved. Issues such as documentation, feasibility, expressiveness, complexity, distribution, performance and scalability are investigated in order to explore the advantages and shortcomings of each system.