Based on above work, we put forward an improved algorithm combined with meta-rule guiding, concept leveling and data cube techniques, which makes the mining algorithm more specific and faster 在此基础上提出了结合元规则指导、概念分层和数据方技术的改进的挖掘算法,使以后的挖掘工作更具有针对性,更加迅速。
The paper propose a new means to mine multidimensional association rules based on multidimensional frequent items set by two steps . firstly we obtain inter-dimension association rules by combining data cube technique with apriori method efficiently 本文中对基于多维的频繁项集的算法进行了探索和算法优化,尤其是通过采用了维搜索和散列的技术方法而使得系统的挖掘性能大大提高。