基于互信息的教育数据矩阵加权正负关联模式发现  

Discovery of Matrix-Weighted Positive and Negative Association Patterns from Educational Data Based on Mutual Information

作　　者：余如[1,2] 黄名选[3] 黄丽霞[4] 

机构地区：[1]广西教育学院文化传播学系,南宁530023 [2]广西教育学院党政办,南宁530023 [3]广西教育学院科研处,南宁530023 [4]广西教育学院教务处,南宁530023

出　　处：《数据采集与处理》2015年第1期219-230,共12页Journal of Data Acquisition and Processing

基　　金：国家自然科学基金(61262028)资助项目;广西自然科学基金(2012GXNSFAA053235)资助项目;广西教育厅科研(2013LX236;201203YB225)资助项目;广西高校优秀人才计划(桂教人[2011]40号)资助项目

摘　　要：本文将互信息模型引入教育数据关联模式挖掘,提出一种基于互信息的教育数据矩阵加权正负关联模式挖掘算法,给出与其相关的定理及其证明。本文算法克服了现有挖掘算法的缺陷,考虑了教育数据项集在学生信息数据库中具有的权值,采用新的正负关联模式评价标准,挖掘出更接近实际情况的正负关联模式。通过关联模式分析,发现教育数据中潜在有用的教育、教学规律和教育发展趋势,为教育管理、教育决策和教学改革提供科学的依据。以真实的教育数据作为实验数据测试集,实验结果表明,本文算法有效,在教育信息化数据处理与分析中具有重要的应用价值。The mutual information model is introduced into the educational data association patterns mining.A new mining algorithm of the matrix-weighted positive and negative association patterns from educational data is presented based on mutual information model,and the related theorems and their proof are given.The algorithm overcomes the defects of the existing algorithms for weighted association patterns.It pays special attention to the various weights of the itemset in database,and also uses a new evaluation standard of positive and negative association patterns.Hence the positive and negative association patterns obtained from the educational data get closer to reality.Analysis on these patterns shows that,the potential educational and teaching rules,as well as educational development trend are discovered,providing a scientific basis for management,decision-making and teaching reform in education.Experiment results on real educational data demonstrate that the proposed algorithm is effective and reliable,with important potential value in the educational data processing and analyzing.

关 键 词：教育数据挖掘 关联规则 负关联规则 矩阵加权模式 互信息 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]