Quality extensions and uncertainty handling for context ontologies
Davy Preuveneers, Yolande Berbers · 2006
Context, by nature, involves real world entities and is therefore subject to uncertainty and inaccuracies. Ontologies are often used to model context in a formal way in order to achieve a shared semantic understanding of concepts and the relationships that hold among them. However, they lack support for representing ambiguous context and appropriate comparison algorithms. As such, context-aware applications may make the assumption that the context they use is completely accurate. In this paper we propose a simple and lightweight yet generic approach to extend context ontologies with quality of context properties and discuss the use of these quality properties for context ontology matching under uncertainty using fuzzy set theory. We illustrate the proposed extensions and uncertainty mechanisms with a small example where uncertain spatiotemporal coverage is combined with other contextual properties.