  When ontologies cover overlapping topics, the overlap can be represented
using ontology alignments. These alignments need to be continuously adapted to
changing ontologies. Especially for large ontologies this is a costly task
often consisting of manual work. Finding changes that do not lead to an
adaption of the alignment can potentially make this process significantly
easier. This work presents an approach to finding these changes based on RDF
embeddings and common classification techniques. To examine the feasibility of
this approach, an evaluation on a real-world dataset is presented. In this
evaluation, the best classifiers reached a precision of 0.8.
