DOME results for OAEI 2018.

DOME (Deep Ontology MatchEr) is a scalable matcher which relies on large texts describing the ontological concepts. Using the doc2vec approach, these texts are used to train a fixed-length vector representation of the concepts. Mappings are generated if two concepts are close to each other in the resulting vector space. If no large texts are available, DOME falls back to a string based matching technique. Due to its high scalability, it can also produce results in the largebio track of OAEI and can be applied to very large ontologies. The results look promising if huge texts are available, but there is still a lot of room for improvement.