Reusing existing Semantic Web ontologies is necessary to avoid heterogeneity as well as redundant modeling efforts, because ontology engineering is a time-consuming and cost-intensive task. In order to decide whether a candidate ontology comprises the right concepts, an analysis process is necessary to understand the conceptual model of the ontology. Driven by the idea that concept grouping simplifies understanding the content of an ontology we investigate the applicability of community algorithms from the field of Social Network Analysis on the graph structure of RDF/XML based OWL documents to identify concept groups. In this paper, we present our experiments with different community algorithms on popular ontologies and compare our results with manually created concept groups.
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