The Internet of Things (IoT) aims at linking smart objects that are relevantto the user and embedding intelligence into the environment. It is more and moreaccepted in the scientific community and expected by end users, that pervasive servicesshould be able to adapt to the circumstances or situation in which a computingtask takes place, and maybe even detect all relevant parameters for this purpose. Workpresented in this paper addresses the challenge of bringing together concepts and experiencesfrom two different areas: context modeling and ontology matching. Currentwork in the field of automatic ontology matching does not sufficiently take into accountthe context of the user during the matching process. The main contributions of thispaper are (1) the introduction of the concept of “context” in the ontology matchingprocess, (2) an approach for context-based semantic matching, which is building on different(weighted) levels of overlap for a better ranking of alignment elements dependingon user’s context, (3) an evaluation of the context-based matching in experiments andfrom user’s perspectives.