摘要
以数字化校园应用为背景,充分利用数据中心存在的大量教学数据,采用数据挖掘技术中的分类技术和关联规则挖掘算法对教学质量评价数据和学生成绩数据进行了挖掘。通过构造决策树挖掘了教师的职称、学位、年龄与教学质量评价结果之间的潜在联系,通过关联分析理论,对学生课程成绩数据库挖掘了专业课程之间的相关性,得到了一些合理、可靠的课程关联规则。实验结果表明,所得出的结论对高校教学和人才培养有一定的指导意义。
This paper based on the application of digital campus, fully utilized amounts of data existing in the data center, adopted classification technology to mine teaching quality evaluation data and association rule mining algorithm to mine students＇ score. By constructing a decision tree, it extracted the relation between the title, degree, age and teaching quality evaluation result, and applied the theory of association rule mining to the students＇ score, discussed the relativity of courses. The paper obtained some reasonable, dependable association rules. Experimental results showed that conclusion obtained had a certain guiding significance in teaching and personnel training.
出处
《实验室研究与探索》
CAS
北大核心
2013年第11期232-236,共5页
Research and Exploration In Laboratory
关键词
数据中心
数据挖掘
分类技术
关联规则
data center
data mining
classification technology
association rule
作者简介
李爱凤（1977-），女，江西新余人，硕士，讲师，主要研究领域为数据挖掘与数据仓库。Tel．：18922168676；E-mail：liar0210@126．com
