Discovery and evaluation of non-taxonomic relations in domain ontologies

Authors:
Albert Weichselbraun;Gerhard Wohlgenannt;Arno Scharl;Michael Granitzer;Thomas Neidhart;Andreas Juffinger
Affiliations:
Institute for Information Business, Vienna University of Economics and Business Administration, Austria.;Institute for Information Business, Vienna University of Economics and Business Administration, Austria.;Department of New Media Technology, MODUL University Vienna, Austria.;Know-Center Graz, Austria.;Knowledge Management Institute, Graz University of Technology, Austria.;Knowledge Management Institute, Graz University of Technology, Austria
Venue:
International Journal of Metadata, Semantics and Ontologies
Year:
2009

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Abstract

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.