Ontology Express: Statistical and Non-Monotonic Learning of Domain Ontologies from Text

Text mining has an important role to play in aiding experts to construct domain specific ontologies by highlighting the important classes, properties and relations that occur within large text collections. In this paper we propose a systematic framework for discovery of ontological types using typing information complemented with statistical filtering. Preliminary experiments are conducted on three corpora in the domain of molecular biology and results show that the top level types we obtain closely meet the intuitions and expectations of domain experts.