摘要
利用可拓数据挖掘,将可拓分类方法应用到高校教师科研考核评价中.对考核结果进行定"量"和定"性"的分析,将教师的科研情况划分为正质变、负质变、正量变及负量变等类型,并计算其支持度和可信度,为科研管理者衡量策略执行效果提供数量化的参考依据.
By means of extension data mining, apply the extension classification method into faculty scientific research evaluation. Analyze the evaluation results quantitatively and qualitatively, and classify the states of faculty＇s scientific research into positive qualitative change, negative qualitative change, positive quantitative change and negative quantitative change types. Then calculate their supports and confidences. This will provide quantified references for scientific research manager to measure the execution effects of strategies.
出处
《数学的实践与认识》
北大核心
2015年第12期53-59,共7页
Mathematics in Practice and Theory
基金
广东省自然科学基金项目(10151009001000044)
关键词
可拓数据挖掘
可拓分类
科研考核
extension data mining
extension classification
scientific research evaluation
