Anchor-Profiles for Ontology Mapping with Partial Alignments Frederik C. Schadd Nico Roos Department of Knowledge Engineering, Maastricht University, Maastricht, The Netherlands Abstract. Ontology mapping is a crucial step for the facilitation of information exchange between knowledge sources. In the industry this process is of- ten performed semi-automatically, with a domain expert supervising the process. Such an expert can supply a partial alignment, known as an- chors, which can be exploited with more elaborate mapping techniques in order to identify the remaining correspondences. To do this we pro- pose a novel approach, referred to as anchor-profiles. For each concept its degree of similarity to each anchor is gathered into a profile for com- parison. We evaluated our approach on the Ontology Alignment Evalua- tion Initiative (OAEI) benchmark dataset using partial alignments that are randomly generated from the reference alignments. The evaluation reveals an overall high performance when compared with mapping sys- tems that participated in the OAEI2012 campaign, where larger partial alignments lead to a higher f-measure. Keywords. semantic web, interoperability, ontology mapping, alignment reuse, anchor profiles 1. Introduction The ability to access and process information is an ever increasing issue due to the rise of the internet and with it the ability to access knowledge sources across the world. While in the past information domains would be modelled using database schemas, recent developments resulted in the proliferation of semantic web tech- nologies for this purpose. Many companies depend on these data solutions for their business operations and services. However, since every user of such tech- nologies has different requirements and views of a given domain, it is likely that he or she would model this domain differently when compared to another user. This leads to the interoperability problem, where the presence of different domain specifications, known as ontologies, prohibits the exchange of information between the two different knowledge sources. As an example, this leads to problems when two businesses want to cooperate and access each other’s knowledge bases, or when one company acquires another and wishes to integrate the new data into its existing knowledge system. In order to circumvent this issue, the heterogeneous ontologies that are em- ployed by the two different knowledge systems need to be mapped, such that for