Ontology Learning for the Semantic Web
IEEE Intelligent Systems
| Hi-index | 0.00 |
The Semantic Web requires automatic ontology population methods. We developed an approach, that given existing ontologies, extracts instances of ontology relations, a specific subtask of ontology population. We use generic, domain independent techniques to extract candidate relation instances from the Web and exploit the redundancy of information on the Web to compensate for loss of precision caused by the use of these generic methods. The candidate relation instances are then ranked based on co-occurrence with a seed set. In an experiment, we extracted instances of the relation between artists and art styles. The results were manually evaluated against selected art resources.