Answer Set Programming for the Semantic Web

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 work 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.

Roman Schindlauer received his PhD from the Vienna University of Technology, where he was a research assistant in the Knowledge-Based Systems Group. He is currently working as a program manager at Microsoft SQL Server in Redmond.