基于OLAP和数据挖掘技术的高考成绩分析

发布时间：2018-06-16 12:08

本文选题：数据挖掘 + 联机分析处理　；参考：《苏州大学》2016年硕士论文

【摘要】：在中国,高考可以算得上是规模最大且最具影响力的人才选拔制度。高考不仅是对高等教育专业人才进行选拔性的一种测试手段,而且是对现在基本课程教学质量的测试,因此高考试卷和高考成绩划分也容易受到异议。江苏省作为全国有名的教育大省,其高考一直颇受关注。本文以江苏省海门市某高中高考考生成绩为实验基础,包括语文、数学、英语三门总分、对应批次等级与两门选修的等级。江苏省高校招生考试除了成绩,还有两个以等级记分的选修课程。通过对已有的考生成绩数据建立数据仓库,应用联机分析处理(OLAP),建立直观的数据视图,创建挖掘模型,通过学生模拟考试成绩去预测他们最后可能的高考成绩。本论文的主要工作包括:1)处理已有高考学生的相关成绩数据。对数据进行统一格式处理,将考生的高考成绩导入数据库中,建立完整的数据仓库,分别对应考生的高考分数、录取等级(高考等第)以及两门高考选修成绩。应用关联规则来挖掘模拟考试以及高考成绩之间的规则。通过建立数据源视图,建立关联规则,从模拟考试和高考的事务集合中挖掘并找出满足置信度和支持度要求的所有链接,挖掘模拟考试成绩与高考成绩之间隐藏的重要关联。2)应用决策树分类来预测高考的录取批次分类预测。即从高考分数、高考等第和高考选修三个方面进行决策树建模,根据已知的模拟考试成绩进行高考成绩的分类预测。将前面关联规则挖掘到的规则应用到决策树分类中,从高考等第、高考选修两个方面,得到应用规则后的决策树分类矩阵,比较两者之间的分类差距。
[Abstract]:In China, the gaokao is arguably the largest and most influential talent selection system. College entrance examination is not only a kind of test means to select the talents of higher education, but also a test of the teaching quality of basic courses, so it is easy to disagree with the classification of the examination papers and the scores of the college entrance examination. Jiangsu Province as a famous education province, its college entrance examination has been quite concerned. Based on the results of a senior high school examinee in Haimen City, Jiangsu Province, this paper is based on the total scores of Chinese, mathematics and English, corresponding batches and two elective grades. In addition to the results, there are two graded elective courses in Jiangsu Province. Through the establishment of data warehouse for existing examinee score data, the application of OLAP, the establishment of intuitionistic data view, the creation of mining model, and the prediction of their final possible college entrance examination results by students' simulated test results. The main work of this thesis includes: 1) dealing with relevant scores of students in college entrance examination. The data are processed in a unified format, and the results of the college entrance examination are imported into the database, and a complete data warehouse is established, which corresponds to the scores of the examinees, the grades of admission (the first one) and the elective grades of the two subjects. The association rules are used to excavate the rules between the simulated test and the score of the college entrance examination. By creating a data source view, establishing association rules, mining and finding all links that meet the confidence and support requirements from the transaction set of mock exams and college entrance exams, Mining the hidden important relation between simulated test scores and college entrance examination scores. 2) applying decision tree classification to predict the matriculation batch classification and prediction of college entrance examination. That is to do decision tree modeling from three aspects of college entrance examination scores, college entrance examination and electives, and then classify and forecast the results of college entrance examination according to the known simulated test results. The rules mined by the former association rules are applied to the decision tree classification. From the two aspects of college entrance examination and college entrance examination, the classification matrix of the decision tree after applying the rules is obtained, and the classification gap between the two is compared.
【学位授予单位】：苏州大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：G632.474;TP311.13

【参考文献】