Title: Discovery and evaluation of non-taxonomic relations in domain ontologies

Authors: Albert Weichselbraun, Gerhard Wohlgenannt, Arno Scharl, Michael Granitzer, Thomas Neidhart, Andreas Juffinger

Addresses: 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

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.

Keywords: ontology learning; ontology extension; link-type detection; non-hierarchical relations; non-taxonomic relations; vector space modelling; domain ontologies.

DOI: 10.1504/IJMSO.2009.027755

International Journal of Metadata, Semantics and Ontologies, 2009 Vol.4 No.3, pp.212 - 222

Published online: 10 Aug 2009 *

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