Enhancing ontology-based context modeling with temporal vector space for ubiquitous intelligence

Context is the information, which is created and obtained from the surrounding environment for the interaction between humans and computational services. A generic model is a key accessor to the context in any context-aware applications for ubiquitous computing. In the past decades, a number of context modeling techniques have been proposed e.g. markup scheme based, logic-based, graphical, and ontology-based. Since ontology in its nature is a promising tool to specify concepts and interrelations, it has been widely adopted in context modeling. However, in the rapid changing environments, semantics may vary according to the time factors and dynamic group of users. In this paper, we propose an ontology-based context model with temporal vector space in order to complement this deficiency.