DocumentCode :
130974
Title :
Application of improved association rule algorithm in the courses management
Author :
Hua Wang ; Ping Liu ; Hongyang Li
Author_Institution :
Inf. Eng. Inst., Capital Normal Univ., Beijing, China
fYear :
2014
fDate :
27-29 June 2014
Firstpage :
804
Lastpage :
807
Abstract :
Apriori is a classical association rule algorithm, On the basis of analyzing the Apriori algorithm and some improved algorithms, Using Matlab tool implements an efficient algorithm, the improved algorithm largely reduces the size of candidate sets and improves the mining efficiency. Finally, the improved algorithm is applied in the university curriculum management, which uses students´ academic records as data source to mining the hidden curriculum related rules. And other relevant metrics such as lift, all confidence and cosine are introduced to verify the correlation of association rules. These will be significance to provide the significance information for teaching management.
Keywords :
data mining; educational administrative data processing; educational institutions; teaching; Matlab tool; apriori algorithm; association rule algorithm; courses management; data source; mining efficiency; students academic records; teaching management; university curriculum management; Apriori algorithm; algorithm efficiency; association rules; course correlation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
Conference_Location :
Beijing
ISSN :
2327-0586
Print_ISBN :
978-1-4799-3278-8
Type :
conf
DOI :
10.1109/ICSESS.2014.6933688
Filename :
6933688
Link To Document :
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