Approach for Discovering Association Rules from Log Ontologies Based on Hybrid System
Zhou Ming-tian · 2009
Building access pattern association rules on top of log ontologies is one of the main tasks of semantic Web usa-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 ILP theory,the access pattern association 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.