Knowledge sifter: Ontology-driven search over heterogeneous databases

Knowledge Sifter is a scaleable agent-based system that supports access to heterogeneous information sources such as the Meb, open-source repositories, XML-databases and the emerging Semantic Web. User query specification is supported by a user agent that accesses multiple ontologies using an integrated conceptual model. A collection of cooperating agents supports interactive query specification, refinement, decomposition, and processing, as well as result ranking and presentation. The Knowledge Sifter architecture is general and modular so that ontologies and information sources can be easily incorporated A proof-of-concept implementation depicts Knowledge Sifter using a domain ontology together with geo-spatial and semantic name services to enhance query formulation and to search image databases such as Lycos and TerraServer.