基于Rough集的数据挖掘在教学评价中的应用  

Application of Rough set based data mining in teaching evaluation

作　　者：周玉敏[1] 

机构地区：[1]重庆邮电大学经济管理学院,重庆400065

出　　处：《重庆邮电大学学报（自然科学版）》2008年第5期627-630,共4页Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition)

摘　　要：基于粗集的数据挖掘的主要过程是数据预处理、约简及规则提取。为了分析教师教学行为和教学效果之间的关系,以教学评价的数据为基础,利用基于粗糙集的数据挖掘技术进行挖掘。实例研究中采用基于分明矩阵的属性约简算法和启发式属性值约简算法,去掉决策表中的冗余属性和属性值,得到了影响教学效果的关键因素和相关规则。The three main steps during data mining based on rough set are data preparation, reduction, and generating rules. In order to find the relationship between the teacher＇s teaching behavior and the teaching effect, the rough set based data mining technology was used based on teaching evaluation data. An attribute reduction algorithm based on discernible matrix and a heuristic value reduction algorithm were adopted to reduce the redundant attribute and attribute value on the decision table, and then the key factor and related rule that affect teaching effects were gained.

关 键 词：粗糙集 属性约简 值约简 规则 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]