Hybrid context modeling: a location-based scheme using ontologies

Context awareness is an inherent feature of pervasive computing. It enhances the proactiveness of the system thus requiring less user attention and fewer human-machine interactions, it supports intelligent personalization features, and it can assist the system to address the user requirements considering the current conditions. Nevertheless, in such environments, various types of context information are involved and need to be efficiently managed and maintained, soundly interpreted, rapidly processed, and securely disseminated by the system. Thus, an interoperable and flexible context representation scheme is necessary that will support efficient context interpretation and reasoning and will perform well in distributed large-scale context-aware systems. This paper is concerned with the development of a hybrid context representation scheme that aims to combine the maintenance, distribution and administrative facilities of a location-based context model and the semantic advantages of context ontologies