Comparison of a Deductive Database with a Semantic Web reasoning engine |
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| Authors: | Simone A Ludwig |
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| Affiliation: | 1. Laboratoire des Sciences de l''Information et des Systèmes (LSIS), UMR CNRS 7296, AMU Domaine universitaire de Saint Jérôme, Avenue Escadrille Normandie Niemen, 13397 Marseille Cedex 20, France;2. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas (CIFASIS), CONICET, UNR, Ocampo y Esmeralda, S2000EZP Rosario, Argentina;1. Department of Information Management, National Chung Cheng University, Chia-Yi County, Taiwan, ROC;2. Department of Information Management and Finance, National Chiao Tung University, Hsinchu City, Taiwan, ROC;3. School of Economics and Business, SUNY at Oneonta, Oneonta, NY 13820, United States;4. Chang-Hua Hospital, Ministry of Health and Welfare, Executive Yuan, Chang-Hua County, Taiwan, ROC;1. Faculty of Engineering and Natural Sciences, Tampere University, Korkeakoulunkatu 6, 33720 Tampere, Finland |
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| Abstract: | 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. |
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