一种新的面向属性归纳中概念层次技术研究  

New concept hierarchy optimization method in attribute-oriented induction

作　　者：孙华梅[1] 郭茂祖[2] 焦杰[2] 黄梯云[1] 

机构地区：[1]哈尔滨工业大学管理学院,哈尔滨150001 [2]哈尔滨工业大学计算机科学与技术学院,哈尔滨150001

出　　处：《管理科学学报》2004年第1期65-72,共8页Journal of Management Sciences in China

基　　金：国家自然科学基金资助项目(70071008);黑龙江省博士后科研启动基金资助项目;哈尔滨工业大学校基金资助项目(HIT.2002.78);国家"863"计划资助项目(2003AA118030).

摘　　要：面向属性归纳的方法目前是数据挖掘主要技术之一.在分析基本的面向属性归纳算法不足的基础上,提出了一种概念层次优化技术,包括:将基于规则的概念图转化成一棵概念树;对于不平衡的概念树,再转化成平衡的概念树;用节点集合来记录数据库中每个元组在概念层次中的泛化路径.利用置信度、支持度和LS充分性因子等评价指标对学习结果进行取舍.最后,将算法在爱尔兰教育经历数据库分析中进行了应用测试,结果显示了算法更加有效,适用性更强.Attribute-oriented induction (AOI) approach is becoming one of the main techniques in data mining. In this paper, the basic AOI algorithm is described and its shortage is given. Then a new concept hierarchy optimization method is presented. The rule-based concept graph is covered into concept tree; the unbalanced tree; is then covered into a balanced tree if concept tree is an unbalanced one; the induction path of each node in the concept tree is recorded as node aggregate. The learning results are evaluated with support, confidence and LS sufficient factor. The algorithm is applied to Irish Educational Transitions Data, and results show that it is more effective and more suitable.

关 键 词：数据挖掘 概念描述 基于规则的面向属性归纳 概念层次 

分 类 号：C931.6[经济管理—管理学]