Improved Knowledge Graph Embedding using Background Taxonomic Information

Understand

Knowledge graphs are used to represent relational information in terms of triples.

• To enable learning about domains, embedding models, such as tensor factorization models, can be used to make predictions of new triples.
• Often there is background taxonomic information (in terms of subclasses and subproperties) that should also be taken into account.
• We show that existing fully expressive (a.k.a.