一种基于异构系统发现日志本体关联规则的方法

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.

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

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.