An Ontology Matching Approach Combining Word Embedding and the Radius Measure

Ontology alignment plays a key role in achieving interoperability on the semantic Web. Inspired by the success of word embeddingtechniques in several NLP tasks, we propose a new ontology alignmentapproach based on the combination of word embedding and the radiusmeasure. We tested our system on the OAEI conference track and thenapplied it to aligning ontologies in a real world case study. The experimental results show that using word embedding and the radius measuremake it possible to determine, with good accuracy, not only equivalencerelations, but also hierarchical relations between concepts.