. (2009). “Discovery and Evaluation of Non-Taxonomic Relations in Domain Ontologies”. International Journal of Metadata, Semantics and Ontologies, 4(3):212-222
The identification and labelling of non-hierarchical relations are among the most challenging tasks in ontology learning. This paper describes a bottom-up approach for automatically suggesting ontology link types. The presented method extracts verb-vectors from semantic relations identified in the domain corpus, aggregates them by computing centroids for known relation types, and stores the centroids in a central knowledge base. Comparing verb-vectors extracted from unknown relations with the stored centroids yields link type suggestions. Domain experts evaluate these suggestions, refining the knowledge base and constantly improving the component's accuracy. A final evaluation provides a detailed statistical analysis of the introduced approach.
Keywords: ontology learning, ontology extension, link type detection, non-hierarchical relations, non-taxonomic relations, vector space model