计算机科学 ›› 2012, Vol. 39 ›› Issue (6): 175-178.

• 数据库与数据挖掘 • 上一篇    下一篇

基于OLAP与数据挖掘的高考招生数据分析

何小明,张自力,肖灿,夏大飞   

  1. (西南大学智能软件与软件工程重点实验室 重庆400715)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Data Analysis on National College Entrance Examination and Admission Using OLAP and Data Mining

  • Online:2018-11-16 Published:2018-11-16

摘要: 如何从海量的高考招生数据中发现有用信息,是招生主管部门迫切关心的问题,也是家长、考生以及社会各界都十分关注的问题。围绕这一问题,依据某省多年来累积的高考招生数据,建立数据仓库和多维数据集,进行OLAP分析与数据挖掘分析,得到了一些潜在的有用信息。研究分析表明,这些信息可以为招生主管部门提供决策支持,也可作为指导考生合理填报志愿的重要依据。介绍了数据仓库和多维数据集的建立过程、录取相关数据的OLAP分析及其结果的解读过程以及利用决策树算法和关联规则算法进行数据挖掘的过程。

关键词: 数据仓库,OI_AP,数据挖掘,决策树,关联规则

Abstract: How to find useful information from massive data of national college entrance examination and admission (NCEEA) is one of the key issues of the provinces and cities admission offices(PCAO),and it also attracts the attention of parents and examinees as well as all sectors of the society. Around this issue, a data warehouse and a data cube were built based on the admission data accumulated over the years in one province. Some potential and useful information was found through OLAP analysis and data mining analysis. Research and analysis represent that these information can provide decision-making support for the PCAO and can be important basis for guiding examinees to choose preference reasonably. This article focused on the process of building data warehouse and cube, the process of OI_AP analysis on admission related data and the result interpretation, the process of data mining by using decision tree algorithm and associate rule algorithm.

Key words: Data warehouse, OLAP, Data mining, Decision tree, Associate rule

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