期刊文献+

利用Apriori算法对医学生成绩进行课程关联性分析 被引量:3

An analysis of curriculum relevance on medical students' achievements by apriori algorithm
下载PDF
导出
摘要 在高校教学管理中,成绩管理非常重要。通过分析成绩数据,挖掘出隐含在成绩数据中的有价值的规律,能辅助教学决策,对专业建设、培养方案制定、课程设置、教学管理等方面具有重要的指导意义。主要运用Apriori算法对学生成绩进行分析,挖掘出有关联性的课程成绩之间的相互规律。 In teaching management of institutions of higher learning, achievement management is of great importance. Analyzing the achievement data to uncover the valuable laws hidden in achievement data can help teaching decisions and have important guiding significance for such aspects as major building, establishment of training program, curriculum setting, and teaching management. This paper mainly utilizes Apriori algorithm to analyze students’ achievements and uncover the mutual laws among relevant courses’ achievements.
作者 牛猛
出处 《河北工程大学学报(社会科学版)》 2015年第2期115-117,124,共4页 Journal of Hebei University of Engineering(Social Science Edition)
关键词 APRIORI算法 成绩 课程关联性 分析 Apriori algorithm achievement curriculum relevance analysis
  • 相关文献

参考文献6

二级参考文献38

  • 1徐章艳,刘美玲,张师超,卢景丽,区玉明.Apriori算法的三种优化方法[J].计算机工程与应用,2004,40(36):190-192. 被引量:71
  • 2张继福,郑链,史虹.联机分析处理与关联规则挖掘的集成化模型研究[J].北京理工大学学报,2005,25(2):121-126. 被引量:6
  • 3佟强,周园春,阎保平.关联规则挖掘算法[J].微电子学与计算机,2005,22(6):68-72. 被引量:21
  • 4RICHARD J.ROIGER,MICHAEL W.GEATZ.著.翁敬农译.数据挖掘教程[M].北京:清华大学出版社,2003.
  • 5[1]C C Aggarwal,P S Yu. Mining Large Itemsets for Association Rules[J].Data Engineering Bulletin, 1998 ;21 ( 1 ) :23~31
  • 6[2]Eui-Hong Han,George Karypis,Vipin Kumar. Scalable Parallel Data Mining for Association Rules[J],IEEE Transactions on Knowledge and Data Engineering,2000; 12(3) :377~352
  • 7[3]R Agrawal,S Srikant.Fast Algorithms for Mining Association Rules[C].Proc.20th Int Conf on VLDB,Santiago,Chile,1994:487~499
  • 8[4]J S Park,M S Chen,P S Yu. An Effective Hash-Based Algorithm for Mining Association Rules[C].Proc ACM SIGMOD Int Conf Management of Data,San Jose,CA, 1995:175~186
  • 9[5]J Liu,J Yin. Towards Efficient Data Re-mining(DRM)[C].Proc PAKDD,5th Pacific-Asia Conf. Hong Kong,China,2001:406~412
  • 10[6]S D Lee,D W Cheung,B Kao.Is Sampling Useful in Data Mining?A Case in the Maintenance of Discovered Association Rules[J].Data Mining and Knowledge Discovery,Kluwer Academic Publishers,1998;2 (3): 233~262

共引文献182

同被引文献15

引证文献3

二级引证文献10

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部