Mining the Content of Relational Databases to Learn Ontologies with Deeper Taxonomies

Relational databases are valuable sources for ontology learning. Previous work showed how precise ontologies can be learned from such structured input. However, a major persisting limitation of the existing approaches is the derivation of ontologies with flat structure that simply mirror the schema of the source databases. In this paper, we present the RTAXON learning method that shows how the content of the databases can be exploited to identify categorization patterns from which class hierarchies can be generated. This fully formalized method combines a classical schema analysis with hierarchy mining in the data. RTAXON is one of the methods implemented in the RDBToOnto tool.