| dc.description.abstract |
Semantic Web ontologies are fast-growing knowledge sources
on the Web. Searching relevant concepts from this large repository is a
challenging problem. The current Semantic Web search engines provide
either (1) coarse-grained search over ontologies or (2) very ne-grained
search over individuals.We believe searching and ranking concepts across
ontologies provides an ideal granularity for certain tasks such as ontology
population and web page annotation. Towards this objective, we
propose a novel approach of indexing concepts using ontology axioms
in an inverted le structure and ranking them using a dynamic ranking
algorithm. Our proposed method is generic and domain-independent. A
preliminary evaluation indicates that our proposed method is e ective,
outperforming the search function of BioPortal, a large and widely-used
ontology repository. |
en_US |