发掘多值属性的关联规则  

An Algorithm for Mining Quantitative Association Rules

作　　者：张朝晖 陆玉昌[1,2] 张钹[1,2] 

机构地区：[1]清华大学计算机科学与技术系 [2]清华大学智能技术与系统国家重点实验室

出　　处：《软件学报》1998年第11期801-805,共5页Journal of Software

基　　金：国家自然科学基金;国防预研基金

摘　　要：属性值可以取布尔量或多值量．从以布尔量描述的数据中发掘关联规则已经有比较成熟的系统和方法，而对于多值量则不然．将多值量的数据转化为布尔型的数据是一条方便、有效的途径．提出一种算法，根据数据本身的情况决定多值量的划分，进而将划分后的区段映射为布尔量，在此基础上可发掘容易理解且具有概括性的、有效的关联规则．An attribute can be Boolean or quantitative. There are lots of systems and methods for mining Boolean association rules but few for quantitative. Mapping quantitative attributes into Boolean attributes is a convenient and efficient way. In this paper, a new clustering algorithm is presented. Quantitative attribute values are partitioned into intervals according to the distribution of them in database. Then the intervals are mapped into Boolean attributes. In this way, quantitative rules can be mined by using the techniques of mining Boolean association rules.

关 键 词：数据采掘 关联规则 数据库 知识发现 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]