Embeds: Scalable, ontology-aware graph embeddings

Abstract

While the growing corpus of knowledge is now being encoded in the form of knowledge graphs with rich semantics, the current graph embedding models do not incorporate ontology information into the modeling. We propose a scalable and ontology-aware graph embedding model, EmbedS, which is able to capture RDFS ontological assertions. EmbedS models entities, classes, and properties differently in an RDF graph, allowing for a geometrical interpretation of ontology assertions such as type inclusion, sub-classing, and alike.