一种基于异构系统发现日志本体关联规则的方法

Approach for Discovering Association Rules from Log Ontologies Based on Hybrid System

构建日志本体之上的访问模式关联规则是语义Web使用挖掘的主要任务之一。在DL-safe规则的限定下,将日志本体和一阶应用规则相结合,构成异构日志知识库,以提高Web日志系统的知识表示和推理能力。在此基础上借助ILP理论从异构日志知识库中挖掘出频繁用户访问模式,并生成访问模式关联规则,以发现用户访问行为之间更丰富的潜在关联知识。该方法提高了语义Web使用挖掘的质量,为改进站点结构提供了更有效的决策知识。实验结果证明了该方法的可行性和有效性。

Building access pattern association rules on top of log ontologies is one of the main tasks of semantic Web usage 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.