关联规则及Apriori算法的大学生行为分析研究

Research on Analysis of College Students' Behaviors Based on Association Rules and Apriori Algorithm

高校中存储着海量数据,但存在数据有效利用不足及不同类型数据关联性较差等问题,在将学生按照智育静态成绩分类后,利用关联规则对大学生的行为数据进行分析,挖掘出不同类型学生在不同行为中存在的区别和联系.实验结果表明,专业课成绩和综合成绩排名有较强联系,班干部的选聘可以参照智育成绩排名,担任班干部对成绩排名影响较小,充分说明利用关联规则能够有效地对大学生行为数据进行挖掘.

There are huge amounts of data stored in colleges and universities. However, due to a series of problems, such as the poor correlation of different types of data, these data are not effectively utilized. After categorizing students according to the static performance of intellectual education, this paper proposes using association rules to analyze their behaviors in order to find the differences and connections between students＇different behaviors. Experimental results show that the professional class scores and comprehensive scores ranking has strong connection, the selections of the cadres can refer to the ranking of the scores of students＇intellects, and being cadres of the class has less influences on their ranking of scores. It also shows that the proposed method can effectively analyze the behavior data of college students.