A fuzzy ontology for semantic modelling and recognition of human behaviour

Abstract

We propose a fuzzy ontology for human activity representation, which allows us to model and reason about vague, incomplete, and uncertain knowledge. Some relevant subdomains found to be missing in previous proposed ontologies for this domain were modelled as well. The resulting fuzzy OWL 2 ontology is able to model uncertain knowledge and represent temporal relationships between activities using an underlying fuzzy state machine representation. We provide a proof of concept of the approach in work scenarios such as the office domain, and also make experiments to emphasize the benefits of our approach with respect to crisp ontologies. As a result, we demonstrate that the inclusion of fuzzy con- cepts and relations in the ontology provide benefits during the recognition process with respect to crisp approaches.