The idea behind the Semantic Web is to add machine-readable meaning to Web pages, enabling the automated interpretation of their semantic content and thus improving the way we express, search, and discover knowledge in the Internet. The Semantic Web requires not only a suitable knowledge representation formalism to describe such data, but also a rule language to specify how to process it. This book represents a contribution to the research efforts of integrating rule-based inference methods with Semantic Web vocabulary languages. The author Roman Schindlauer first introduces the concepts, benefits, and challenges of such a combination in general. He then proposes a novel integration of logic programming under the answer-set semantics with the Web ontology language OWL. Moreover, he outlines a prototype implementation and presents use cases on the basis of concrete, real-world scenarios. This book is intended for researches and professionals in the areas of logic programming and Semantic Web reasoning.
The idea behind the Semantic Web is to add machine-readable meaning to Web pages, enabling the automated interpretation of their semantic content and thus improving the way we express, search, and discover knowledge in the Internet. The Semantic Web requires not only a suitable knowledge representation formalism to describe such data, but also a rule language to specify how to process it. This book represents a contribution to the research efforts of integrating rule-based inference methods with Semantic Web vocabulary languages. The author Roman Schindlauer first introduces the concepts, benefits, and challenges of such a combination in general. He then proposes a novel integration of logic programming under the answer-set semantics with the Web ontology language OWL. Moreover, he outlines a prototype implementation and presents use cases on the basis of concrete, real-world scenarios. This book is intended for researches and professionals in the areas of logic programming and Semantic Web reasoning.
Answer set programming (ASP) is a programming methodology oriented towards combinatorial search problems. In such a problem, the goal is to find a solution among a large but finite number of...
Representing and Utilizing Changing Historical Places as an Ontology Time Series.- Semantic Referencing of Geosensor Data and Volunteered Geographic Information.- SPARQL-ST: Extending SPARQL to...
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