Knowledge Discovery In Ontologies

Ontologies allow us to represent knowledge and data in implicit and explicit ways. Implicit knowledge can be derived by means of several deductive logic-based processes. This paper introduces a new way for extracting implicit knowledge from ontologies by means of a link analysis of the T-box of the ontology integrated with a data mining step on the A-box.The implicit knowledge extracted is in the form of "Influence Rules" i.e. rules structured as: if property p(1) of concept c(1) has value upsilon(1), then property p(2) of concept c(2) has value upsilon(2) with probability pi.The technique is completely general and applicable to whatever domain. The Influence Rules can be used to integrate existing knowledge or to support any other data mining process.A case study about an ontology that describes intrusion detection is used to illustrate how the method works.