Abstract: Building access pattern association rules on top of log ontologies is one of the main tasks of semantic Web user ge mining. With the restrictions of DL-safe rules, we combined log ontologies with first order application rules to build a hybrid log knowledge base. It can improve the capability of knowledge representation and reasoning of Web log system.After mining the frequent user-access patterns from the hybrid system through II_P theory,the access pattern associalion rules can be constructed to discover the potential associations between user-access behaviors. This method improves the results of semantic Web usage mining and provides more decision-making for optimizing the structure of Web sites.The experimental results show that this method is effective and quite feasible to solve practical problems.

Key words: Semantic Web usage mining, Log ontology, Hybrid system, Association rule, Inductive logic programming(ILP)