A New Method For Rules Dependency Extraction

Autonomous systems consist of agents that have access to interpretable information allowing them to make intelligent decisions. This requires the systems to have a good semantic knowledge base. A good semantic knowledge repository has to be backed by a well-defined domain ontology. For the sake of decidability, ontology languages do not provide the required expressiveness. Rules present an efficient support thereby enabling even better decision making. Their complexity and their exponentially growing number imply the need for an automatic management. In this paper, we introduce a new method for the automatic dependency extraction among rule bases associated to ontologies. This is founded on a novel technique of dependency extraction. A prototype of our proposal was implemented and applied on two different rule bases associated to ontologies from different domains. Our results succeeded in increasing the number of the extracted dependency relationships.