attribute association meaning in Chinese

属性关联

This part put forward the system conception of kdd and the apriori algorithm . then evolved the create - frequent - set algorithm which was fit for the freight agent management system . because of the shortage of efficiency , 1 improved the algorithm . because some of the items were not boolean variables , 1 need the quantitaitve attributes association rules discovering algorithm . in general , there had the levels among the items , so multilevel association rules existed . after perfecting the algorithmic need interpret and evaluate the knowledge . in the end , 1 discussed the privacy and security of kdd . the fifth part described the future problems and prospect
第四章是论文的主体，着重介绍知识发现的全过程，按照semma方法论首先进行数据准备，然后进入数据挖掘阶段，提出知识发现的概念体系和公认的apriori算法，从该算法演变出适合于货代管理系统的生成频繁项目集的算法；因为在实际应用中存在效率上的不足，因此进一步地提出了改进方案；在事务处理中各个项目并不都是布尔型变量，因此需要特定的针对多值属性的关联规则发现算法；通常情况下，项目之间存在有层次关系，因此多层次关联规则的发现普遍存在；算法完善并运行后需要对发现的知识进行解释和评估；本章的最后讨论了知识发现的私有性和安全性问题；第五章讲述有待解决的问题和发展前景。