DocumentCode :
3316123
Title :
An Apriori-Based Approach for Teaching Evaluation
Author :
Deng, Jiabin ; Hu, JuanLi ; Chi, Hehua ; Wu, Juebo
fYear :
2010
fDate :
23-25 July 2010
Firstpage :
1
Lastpage :
4
Abstract :
Intelligent evaluation, as an important branch in the field of artificial intelligence, is a decision-making process of simulating the domain experts to solve complex problems. In this paper, we puts forward a kind of intelligent evaluation method based on improved Apriori, which can be used to mine different levels of association rules and evaluate the teaching quality automatically. Firstly, we do some improvement on traditional Apriori algorithm due to its shortcomings. Secondly, we describe the procedure of the teaching quality evaluation based on such improved algorithm. Finally, we give an example and the results show that this method is feasible and effective.
Keywords :
Algorithm design and analysis; Artificial intelligence; Association rules; Clustering algorithms; Data mining; Databases; Education; Frequency; Laboratories; Remote sensing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Engineering and Electronic Commerce (IEEC), 2010 2nd International Symposium on
Conference_Location :
Ternopil, Ukraine
Print_ISBN :
978-1-4244-6972-7
Electronic_ISBN :
978-1-4244-6974-1
Type :
conf
DOI :
10.1109/IEEC.2010.5533217
Filename :
5533217
Link To Document :
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