Concept hierarchy as background knowledge. Relational Database (RDB) has been widely used as the back- end database of information system. Contains a wealth of high- quality information, RDB provides conceptual model and metadata needed in the ontology construction. However, most of the existing ontology building approaches convert RDB schema without considering the knowledge resided in the database. This paper proposed the approach for ontology extraction on top of RDB by incorporating concept hierarchy as background knowledge. Incorporating the background knowledge in the building process of Web Ontology Language (OWL) ontology gives two main advantages: (1) accelerate the building process, thereby minimizing the conversion cost; (2) background knowledge guides the extraction of knowledge resided in database. The experimental simulation using a gold standard shows that the Taxonomic F- measure (TF) evaluation reaches 9.
Relation Overlap (RO) is 8. In term of processing time, this approach is more efficient than the current approaches. In addition, our approach can be applied in any of the fields such as e. Goverment, e. Commerce and so on. This review covers journal articles and conference proceedings published within the last decade. A practical ontology matching system. Proceedings of the 3rd International Conference on Automotive User Interfaces. Symposium Proceedings, 2014 IEEE.
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