AgreementMakerDeep (AMD) is a new flexible and extensible ontology matching system with knowledge graph embedding techniques. AMD learns from classes and their relations between classes by constructing vector representations into the low dimensional embedding space with knowledge graph embedding methods. The results demonstrate that AMD achieves a competitive performance in a few OAEI tracks, but AMD has limitations for property and instance matching. Code is avaiable HERE

Achievement

AMD is among the top fastest system in this Anatomy track. Other performance can be found here

*This work is dedicated to the memory of Isabel F. Cruz.