Web日志中有趣关联规则的发现

Discovery of Interesting Association Rules in Web Log Data

关联规则挖掘是Web用法挖掘的一个重要研究课题 目前的Web日志关联规则挖掘算法忽略了用户对规则是否感兴趣这一重要问题 对Web日志关联规则挖掘算法进行了研究 ,结合网络拓扑结构 ,提出了Web拓扑概率模型和有趣关联规则 (IAR)算法 利用Web拓扑概率模型对关联规则进行有趣度评价 ,得出有趣度高的规则 ,用于改善网络性能 实验显示了IAR算法如何提高规则的利用率和有效地改善网络拓扑

Mining of association rules is an important research topic in web usage mining Currently, web log association rules mining algorithms neglect an important problem of whether users are interested in the rules or not web log association rules mining algorithms are studied Combined with web topology structure, a web topology probability model and an interesting association rules (IAR) algorithm are presented Using web topology probability model to evaluate association rules' interest, IAR gains high interest rules, which can be used to improve network performance The experiment shows how IAR enhances rules'utilization and effectively improves web topology It can be successfully applied to web usage mining