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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jian Wang Zhubin Lu Weihua Wu Yuzhou Li |
| Copyright Year | 2012 |
| Description | Author affiliation: College of Applied Technology, Southwest University, Chongqing, China (Jian Wang; Zhubin Lu; Weihua Wu; Yuzhou Li) |
| Abstract | Data mining deepens the data analysis, also is able to mine the interesting mode hiding in mass data automatically. As a new data analysis technology, data mining makes full use of the modern software technology and computer scientific knowledge, has the extremely important research significance, provides for researchers of various fields with a new intelligence means to realize and use data. In data mining, association rule learning is a popular and well researched method for discovering interesting relations between variables in large databases. This paper makes a series of data analysis and research on the application of data mining technology in the students' scores. This paper use Apriori algorithm of association rules to analyze the intrinsic link among various courses, dig out the precedence relationship and association of students' learning courses, reveal the teaching regularities and problems from large amount of data, as well as to provide a strong basis for reasonable course-setting. |
| Starting Page | 652 |
| Ending Page | 657 |
| File Size | 125810 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467302418 |
| e-ISBN | 9781467302425 |
| DOI | 10.1109/ICCSE.2012.6295159 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-07-14 |
| Publisher Place | Australia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Itemsets Education Data Mining Association Rule Association rules Frequent Itemsets |
| Content Type | Text |
| Resource Type | Article |
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