When developing semantic applications, the construction
of ontologies is a crucial part. We are developing a semiautomatic
ontology construction approach, OntoCase, relying
on ontology patterns as additional resources. A crucial
part of this approach is how to select the appropriate patterns
based on the input representation extracted from a
text corpus. In this paper, we suggest a pattern ranking
and selection approach with the ability to partially bridge
the gap between abstract patterns and specific terms, as well
as being specifically tuned to the characteristics of ontology
patterns. Compared to existing ontology ranking schemes
our approach adds indirect matching of terms as well as relation
matching. An initial experiment indicates that Onto-
Case ranking performs better, especially when ranking small
and abstract patterns, than existing ranking approaches.
2008. p. 2248-