Combining Ontologies and Rules: 2 Example Approaches
| Stijn Heymans | SemanticBits LLC | [Home Page] |
Notice: Hosted by Vinay Chaudhri.
Date: Monday August 22, 2011 at 10:00
Location: EJ228 (SRI E building) (Directions)
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The problem of combining ontologies (in the form of Description Logics knowledge bases) with rules (in the form of Logic Programming rules) evolves around 2 distinct approaches: a tightly-integrated approach and a loosely-coupled approach. In the presentation, we will define the distinguishing features of those approaches. In particular, we will pick an exemplary framework from each approach: Open Answer Set Programming as an implementation vehicle for tightly-coupled approaches and DL-programs as an example of a loosely-coupled approach. We will define these 2 frameworks and analyze some of its key properties, including expressiveness and complexity. Furthermore, we will indicate what the state-of-the-art with respect to these approaches is and what the possible directions for future work are. |
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Dr. Heymans obtained in 2006 a PhD in Theoretical Computer Science from the Free University of Brussels, Belgium, on the integration of ontologies and rules. From 2006 to 2008, he was a PostDoc researcher at the Digital Enterprise Research Institute, Austria. In Innsbruck, he led a research team of researchers in several European Union projects. He was a work package leader in the SUPER project on using semantics for business processes. In 2008-2011, he was the Principal Investigator for an Austrian research project (``Distributed Open Answer Set Programming'') as well as the local project manager for the EU project OntoRule at the Vienna University of Technology with the group of Prof. Thomas Eiter. Currently, he is a Semantic Architect at SemanticBits LLC, United States, a company specialized in health care solutions. Dr. Heymans authored 53 publications (his h-index is 15), organized 4 workshops, and was in the Program Committee of 27 international workshops and conferences. His specialty is in Artificial Intelligence and Semantic Technologies research, in particular Knowledge Representation and Reasoning using formal languages such as Description Logics and Logic Programming. |
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