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Titlebook: Canadian Semantic Web; Mamadou Tadiou Koné,Daniel Lemire Conference proceedings 2006 Springer-Verlag US 2006 Canadian.Kone.Resource Descri

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A. Brennauer,S. Dove,A. Buschauertologies can be attached to a learning object. In light of this, our paper describes a practical approach that makes use of the IEEE LOM standard and which allows multiple ontologies to be included in the markup of learning objects.
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https://doi.org/10.1007/978-3-642-78480-4ts of existing frameworks for DLs with uncertainty in a generic way. Using this as a basis, we then discuss ways to extend these components with uncertainty, which includes the description language, the knowledge base, and the reasoning services. Detailed explanations and examples are included to describe the proposed completion rules.
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Incorporating Multiple Ontologies into the IEEE Learning Object Metadata Standardtologies can be attached to a learning object. In light of this, our paper describes a practical approach that makes use of the IEEE LOM standard and which allows multiple ontologies to be included in the markup of learning objects.
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DatalogDL: Datalog Rules Parameterized by Description Logicsveloped techniques, we present a principled approach to enrich (RuleML) rules with information from (OWL) ontologies, and develop a prototype system integrating a rule engine (OO jDREW) with a DL reasoner (RACER).
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Resolution Based Explanations for Reasoning in the Description Logic ,vious work and present an algorithm that generates explanations for unsatisfiability and inconsistency reasoning in the description language .. The main advantage of our approach is that it is independent of any specific DL reasoners.
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