基于兴趣度的课程关联规则模式研究

On Correlation between Interest Degree and Courses Association Rules

基于关联规则挖掘理论,在原有Apriori算法的基础上引入了兴趣度的概念。针对高校历届学生专业修读课程及考试成绩的海量数据库中挖掘出来的相关课程数据、规律和模式进行了相应的兴趣度分析,进而获取了满足高校教学管理与改革需要的课程相关先修相关规则,以在一定程度上避免学生选课的盲目性。此规则对高校教育体制的改革、学分制的推广及学生个性化学业修读计划的制订与实施等具有积极指导作用。

Based on the association rule mining theory and Apriori algorithm, the paper conducts the interest correlation degree analysis of the related data, rules and modes that are mined from data base of courses and their test grades of graduated students in colleges. Then it offers effective references for college education management and reform. It is also significant for the guidance of course selection and person- al profession planning for students under the credit system.