Ontologies are widely used for capturing and organizing knowledge of a particular domain of interest. This knowledge is usually evolvable and therefore an ontology maintenance process is required. In the context of ontology maintenance we tackle the problem that arises when an instance/individual is written differently (grammatically, orthographically, lexicographically), while representing the same entity/ concept. This type of knowledge is captured into a semantic relationship and constitutes valuable information for many intelligent methods and systems. We enrich a domain ontology with instances that participate in this type of relationship, using a novel name matching method based on machine learning. We also show how the proposed method can support the discovery of new entities/concepts to be added to the ontology. Finally, we present experimental results for the enrichment of an ontology used in the multi-lingual information integration project CROSSMARC.
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