The Internet of Things (IoT) aims at linking smart objects that are relevant to the user and embedding intelligence into the environment. It is more and more accepted in the scientific community and expected by end users, that pervasive services should be able to adapt to the circumstances or situation in which a computing task takes place, and maybe even detect all relevant parameters for this purpose. Work presented in this paper addresses the challenge of bringing together concepts and experiences from two different areas: context modeling and ontology matching. Current work in the field of automatic ontology matching does not sufficiently take into account the context of the user during the matching process. The main contributions of this paper are (1) the introduction of the concept of "context" in the ontology matching process, (2) an approach for context-based semantic matching, which is building on different (weighted) levels of overlap for a better ranking of alignment elements depending on user's context, (3) an evaluation of the context-based matching in experiments and from user's perspectives.

Internet of Things, context-aware computing, ontology matching