并发序列模式挖掘在学生成绩分析中的应用

The Application of Concurrent Sequential Pattern Mining in the Students Scores

将并发序列模式挖掘应用于学生成绩分析,可以帮助高校调整教学内容,预测学生学习效果,从而促进学生的学习和教学质量的提高.以学生各学期科目成绩为数据源,设计实现算法BV,在挖掘得到序列模式的基础上,计算每个客户序列的分支向量,并以此为基础进行并发序列模式挖掘.通过实验可以看出,在时间效率上,改进算法优于支持向量的并发序列模式挖掘算法;课程成绩并发序列模式随着并发度和支持度的不断增大,在某一取值处,达到峰值,然后逐渐减少;算法在高校学生科目成绩上进行实验,得到了有指导意义的并发集.

Concurrent sequential pattern mining is applied to the analysis of the students scores,which can help colleges adjust the teaching contents,predict students＇ learning effect,thus,to promote students＇ learning and the improvement on teaching quality. As the data source with grades of students each semester,design the algorithm of BV,on the basis of getting sequence pattern mining calculate the branch vector of each client pattern,then,starting mining the concurrent sequential pattern. The algorithm has been used for the grades of college students,and a guiding significance to the set of concurrence is got. Concurrent sequential patterns of the grades,with the increase of concurrence and support,arriving at a peak somewhere,then gradually reducing.