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基于约束的关联挖掘在教学信息中的应用研究

the Application and Research of Constraint-Based Association Mining in Teaching Information Databases
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摘要 进行关联规则挖掘时会得到大量的规则,而真正关注的规则往往淹没其中。本文通过对基于约束的关联规则挖掘方法的分析和研究,结合实际学生选课信息,提出了适合的约束条件来剪除无兴趣规则,并挖掘出部分课程间的有趣规则,为今后的教学课程设置提供了参考。 There are too many rules to discover the interesting rules concerned really when mining association rules. This paper analyzes and researches into methods of mining association rules based on constraint conditions, then applies them in analysis of course-selecting information, proposes some proper constraints to prune the uninteresting rules and discovers the useful rules about some courses, which can provide consults for setting courses in the future.
作者 李湘军 黄燕
机构地区 中国农业大学信息与电气工程学院计算机系
出处 《科技广场》 2005年第6期34-38,共5页 Science Mosaic
关键词 数据挖掘 关联规则 兴趣度 Data Mining Association Rules Interestingness
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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科技广场
2005年 第6期

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