摘要
为有效利用高等学校教学管理工作多年来积累的大量数据 ,利用数据挖掘技术 ,对北京地区高等学校1996— 2 0 0 1年毕业生数据库 (BeijingGraduationDatabase ,BGD)进行了数据挖掘研究。采用多种数据预处理方法对原始BGD数据进行了处理 ,提出并利用FAP方法进行了属性构造 ;对关联规划挖掘常用的Apriori算法进行了改进 ,以此为基础根据实际需要设计并实现了关联规则挖掘系统 ;利用所实现的系统对GBD数据库进行挖掘分析 ,得到了有益于高等学校教学管理决策及毕业生就业指导的挖掘结果。
To utilize the data accumulated by universities about pedagogic management effectively, the BGD(Beijing Graduation Database, BGD from 1996 to 2001) was researched by using DM(Data Mining) method. After thorough analysis of BGD,BGD was preprocessesd by many methods to standardize this method and it is made fit for knowledge discovery. In the pro-management progress, FAP method was put forward and adopted, which is used to construct attributes. Association Rules was researched and Apriori algorithm was improved. Association Rule was designed and realized according to practical requirement on the base of improved Apriori algorithm. It is used to mine BGD and some results which is helpful to decision making of universities.
出处
《中国农业大学学报》
CAS
CSCD
北大核心
2003年第2期39-41,共3页
Journal of China Agricultural University
