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 在此基礎(chǔ)上提出了結(jié)合元規(guī)則指導(dǎo)、概念分層和數(shù)據(jù)方技術(shù)的改進(jìn)的挖掘算法,使以后的挖掘工作更具有針對性,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 本文中對基于多維的頻繁項(xiàng)集的算法進(jìn)行了探索和算法優(yōu)化,尤其是通過采用了維搜索和散列的技術(shù)方法而使得系統(tǒng)的挖掘性能大大提高。