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 sort of link analysis of the T-box of the ontology integrated with a data mining step on the A-box. The implicit extracted knowledge has the form of In uence Rules" i.e. rules structured as: if the property p1 of concept c1 has value v1, then the property p2 of concept c2 has value v2 with probability . The technique is completely general and applicable to whatever domain. The In uence Rules can be used to integrate existing knowledge or for supporting any other data mining process. A case study about an ontology describing intrusion detection is used to illustrate the result of the method.