OWL-based reasoning with retractable inference
Carlo Jelmini, Stéphane Marchand‐Maillet · Archive ouverte UNIGE (University of Geneva) · 2004
As a solution to maintain, process and enrich knowledge in the multimedia description framework we are constructing, we propose a forward chaining knowledge base and reasoning engine, supporting RDF documents and OWL Lite ontologies, with the ability to perform non-monotonic, retractable inference. Within our framework, the knowledge over the media collection can be collected in several ways. As we cannot wait for the system to reach an hypothetical state where full knowledge is available, the system has to be able to reason over incomplete knowledge and produce tentative conclusions. As more knowledge is collected over the collection, some of the conclusions need to be retracted from the knowledge base and other conclusions inferred.