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2009 WRI World Congress on Computer Science and Information Engineering
Research on Early-Warning Model of Students' Academic Records Based on Association Rules
Los Angeles, California USA
March 31-April 02
ISBN: 978-0-7695-3507-4
Association Rules is an important research direction of data mining. Its study is mostly concentrated on improving algorithm efficiency presently, but neglects users’ understanding and participating in excavating course. Students’ 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 trainings’ quality.
Index Terms:
Association rules, Apriori algorithm, Interest measure, Early-warning of students' academic records
Citation:
Li Zhu, Yanli Li, Xiang Li, "Research on Early-Warning Model of Students' Academic Records Based on Association Rules," csie, vol. 4, pp.121-125, 2009 WRI World Congress on Computer Science and Information Engineering, 2009
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