관계형 데이터베이스를 이용한 효율적인 OWL 속성 추론 기법

Abstract

AbstractThe Web Ontology Language (OWL) has become the W3C recommendation for publishing and sharing ontologies on the Semantic Web. To derive hidden information from OWL data, a number of OWL reasoners have been proposed. Since OWL reasoners are memory-based, they cannot handle large-sized OWL data. To overcome the scalability problem, RDBMS-based systems have been proposed. These systems store OWL data into a database and perform reasoning by incorporating the use of a database. However, they do not consider complete reasoning on all types of properties defined in OWL and the database schemas they use are ineffective for reasoning. In addition, they do not manage updates to the OWL data which can occur frequently in real applications. In this paper, we compare various database schemas used by RDBMS-based systems and propose an improved schema for efficient reasoning. Also, to support reasoning for all the types of properties defined in OWL, we propose a complete and efficient reasoning algorithm. Furthermore, we suggest efficient approaches to managing the updates that may occur on OWL data. Experimental results show that our schema has improved performance in OWL data storage and reasoning, and that our approaches to managing updates to OWL data are more efficient than the existing approaches.