OntoCase-Automatic Ontology Enrichment Based on Ontology Design Patterns

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OntoCase is a framework for semi-automatic pattern-based ontology construction. In this paper we focus on the retain and reuse phases, where an initial ontology is enriched based on content ontology design patterns (Content ODPs), and especially the implementation and evaluation of these phases. Applying Content ODPs within semi-automatic ontology construction, i.e. ontology learning (OL), is a novel approach. The main contributions of this paper are the methods for pattern ranking, selection, and integration, and the subsequent evaluation showing the characteristics of ontologies constructed automatically based on ODPs. We show that it is possible to improve the results of existing OL methods by selecting and reusing Content ODPs. OntoCase is able to introduce a general top structure into the ontologies, and by exploiting background knowledge the ontology is given a richer overall structure.

This research was primarily conducted at the Information Engineering research group, Jönköping University (SE). Financially supported through projects SEMCO (KK-foundation grant no. 2003/0241), MediaIlLOG (grant from Carl-Olof och Jenz Hamrins Stiftelse), and DEON (STINT). Evaluations were also conducted within the NeOn project, funded by the European Commission, grant no. IST-2005-027595.