DocumentCode :
2633666
Title :
Research on Early-Warning Model of Students´ Academic Records Based on Association Rules
Author :
Zhu, Li ; Li, Yanli ; Li, Xiang
Author_Institution :
Sch. of Comput., China Univ. of Geosci., Wuhan, China
Volume :
4
fYear :
2009
fDate :
March 31 2009-April 2 2009
Firstpage :
121
Lastpage :
125
Abstract :
Association rules is an important research direction of data mining. Its study is mostly concentrated on improving algorithm efficiency presently, but neglects userspsila understanding and participating in excavating course. Studentspsila historical academic records stored in university´s educational administration systems was taken as data source, the paper established interactive visible mining model based on classical association rules, and introduced objective interest degree and subjective interest degree. Experiment results show that model built was feasible and meaningful; it could help us improve teaching management and personnel trainingspsila quality.
Keywords :
data mining; educational administrative data processing; teaching; association rules; data mining; early-warning model; interactive visible mining model; personnel training quality; student academic record; teaching management; university educational administration system; Association rules; Computer science; Data engineering; Data mining; Education; Geology; Management training; Relational databases; Testing; Training data; Apriori algorithm; Association rules; Early-warning of students´ academic records; Interest measure;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
Type :
conf
DOI :
10.1109/CSIE.2009.282
Filename :
5170973
Link To Document :
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