基于数据仓库和数据挖掘的高校教学管理决策支持系统 (1).pdf

南京航空航天大学 硕士学位论文 基于数据仓库和数据挖掘的高校教学管理决策支持系统 姓名：巫红霞 申请学位级别：硕士 专业：计算机应用技术 指导教师：谢强 20081101 南京航空航天大学硕士学位论文 i 摘 要 根据目前的教学管理的现状和需要，教学管理人员和领导希望借助信息技术手段，建立教 学数据运行中心和教学决策支持系统，提供对教学历史数据分析的功能教学管理人员与领导 可以通过该系统及时方便地了解信息，充分发挥历史数据的作用，通过对各种数据的多维分析 和挖掘，可以从中得出一些结论与规律，这些结论与规律应用到教学管理中，可以提高高校办 学水平和管理水平，以及教学决策能力 为了实现高校教学管理决策系统，本文将数据仓库技术和数据挖掘技术引入到高校教学管 理系统中首先分析了现有高校教学管理系统中存在的问题，给出了基于数据挖掘技术的高校 教学管理系统框架，并详细描述了框架的各个组成部分接着深入研究了该框架中的两个关键 技术：数据仓库技术和数据挖掘技术根据教学管理决策支持系统的要求，对经典的 Apriori 算法进行了改进，并将其应用到教学管理相关数据的挖掘中，获得了具有一定指导价值的管理 规则。

最后，实现了基于数据仓库和数据挖掘的高校教学管理系统，并将其应用到具体的项目 中，取得了较好的效果 关键词关键词：：高校教学管理，数据仓库，数据挖掘，关联规则，决策支持 基于数据仓库和数据挖掘的高校教学管理决策支持系统 ii Abstract Based on the actuality and needs of teaching management, the staff and leader hope to set up the data center of teaching and decision support system of teaching management to provide the functions of analysis of data using information technology. They can gain the information easily by using this system and the history data can exert fully its value; By OLAP and data mining to every kind of data, they can get some conclusions and rules to help make decisions. These conclusions and rules can be applied in the teaching management to improve the level of run and management of university, as well as the ability of making decision of teaching management. In order to realize decision support system of university teaching management, Data Warehouse technique and Data Mining technique are applied to system of university teaching management. Firstly, the problems of the current system of university teaching management are analyzed, and the framework of the system of university teaching management based on Data Mining technique is given out, then every part of this framework is described in detail. Secondly, two key techniques: Data Warehouse technique and Data Mining technique are studied in depth. Based on the needs of the decision support system in teaching management , the classical Apriori algorithm was improved, and was applied to teaching management-related data mining, obtaining the management rules of certain value .At the end of the paper, Decision Support System of university teaching administration based on Data Warehouse and Data Mining technique is realized and is applied to a specific project, It obtains good results. Keywords: University Teaching Management, Data Warehouse, Data Mining, Association Rule, Decision Support 基于数据仓库和数据挖掘的高校教学管理决策支持系统 vi 图表清单 图 1.1 教学管理功能模块....................................................................................................................6 图 1.2 教学管理数据业务流程............................................................................................................7 图 1.3 高校教学管理决策支持系统体系结构....................................................................................8 图 2.1 高校教学管理决策支持系统框架..........................................................................................14 图 2.2 一个典型数据立方体..............................................................................................................18 图 2.3 切片操作 .................................................................................................................................18 图 2.4 旋转操作 .................................................................................................................................18 图 2.5 钻取操作 ..................................................................................................................................19 图 3.1 高校教学管理决策支持系统主题域树状结构......................................................................22 图 3.2 招生决策数据仓库信息包......................................................................................................23 图 3.3 成绩主体雪花模型...................................................................................................................24 图 3.4 成绩维度外键关系..................................................................................................................25 图 3.5 成绩数据仓库的星型模型......................................................................................................25 表 3.1 部分信息在不同主题中的粒度级别......................................................................................26 图 3.6 时间维 .....................................................................................................................................26 图 3.7 教学单位维 .............................................................................................................................27 图 3.8 教师维 .....................................................................................................................................27 图 3.9 课程维 .....................................................................................................................................27 图 3.10 学籍信息数据分析模型........................................................................................................28 图 3.11 教学质量评价数据分析模型........................................。