An Ontology-Based System for Semantic Query over Heterogeneous Databases

With an exponential growth in the amount of information available in diverse domains, the traditional information retrieval (IR) approaches which based on keywords can not meet the semantic needs of users. Semantic query, as an application of semantic Web, has shown significant potential in improving the performance of IR. However, many current semantic query engines focus only on the ontology query, while in real world lots of data is stored in heterogeneous relational databases, not ontologies. So how to use semantic query to search the real information in databases has become an issue. In this paper, we explore a novel semantic search approach based on ontology, which uses SPARQL to query the Global Ontology, and realizes the final search of information in the heterogeneous relational databases through a series of query rewrite. A prototype system named ´OSEQ´ has been implemented in light of this approach. And it is illustrated by a case study in the e-commerce domain.