National Great Project of Scientific; Technical Supporting Programs - Ministry of Science & Technology of China During the 11th Five-year Plan [2006BAH02A24, 2006BAJ07B06]; Natural Science Foundation of Hubei Province [2006ABC011]
机构署名:
本校为第一且通讯机构
院系归属:
教育信息技术学院
摘要:
Because of its important application value in almost every region, early-warning has received extensive concern. This paper puts forward a study early-warning mechanism based on association rules. It uses an Apriori mining algorithm with some corresponding restrictions to dig out the latent school record association rules from former students' scores which are viewed as a history resource. Then these rules will be used to match up the data sets that need to monitor. Once a record is matched to one of these rules, the student of this record will receive an early-warning. This kind of early-warn...