改进Apriori算法及其在信息学奥赛学员选拔中的应用
发布时间:2018-02-16 07:02
本文关键词: 数据挖掘 关联规则 Apriori算法 出处:《华侨大学》2015年硕士论文 论文类型:学位论文
【摘要】:数据挖掘是人工智能研究领域的重点,关联规则则是其研究的主要方向。近年来关联规则已被广泛应用在市场营销、科研、医疗、网络入侵检测、教育等领域,并取得了一定的成果。随着信息学奥赛的深入开展,信息学奥赛在学校教育中越来越受到重视。但其只是适合少部分优秀学生的精英教育。由于信息学不是高考学科,在开展过程中遇到诸多挑战。选拔好的苗子对竞赛成功能取到事半功倍的效果,因此将数据挖掘技术运用于信息学奥赛学员的选拔中,利用挖掘结果可促进奥赛良性发展。本文以面向信息学奥赛学员的调查问卷为数据样本,将改进的Apriori算法应用于信息学奥赛学员的选拔中。主要内容包括:1.论述Apriori算法的主要思想、执行过程、遇到的瓶颈和已有改进方法。2.提出一种改进算法Tire-Apriori,介绍了改进算法基于字典树及事务投影的基本思想、理论依据以及结合实例详细分析了算法的执行步骤;运用c++语言编写算法程序,用实验验证Tire-Apriori算法的优势。3.Tire-Apriori应用于选拔信息学奥赛学员。以本文设计的调查问卷为数据源,分析了数据的采集及预处理过程;采用Tire-Apriori,分两种情况对数据进行挖掘:第一,挖掘“获奖与学生特征的关系”,为信息学奥赛教练挑选学员提供了选拔的标准;第二,挖掘“信息学奥赛与素质教育的关系”,吸引更多有能力参加竞赛的学员自愿参与到竞赛团队中。
[Abstract]:In recent years, data mining has been widely used in marketing, scientific research, medical treatment, network intrusion detection, education and other fields. With the further development of the Olympiad of Informatics, it has received more and more attention in school education. But it is only an elite education suitable for a small number of excellent students. Since informatics is not a subject of the college entrance examination, In the process of development, there are many challenges. The selection of good seedlings can achieve twice the result with half the effort, so the data mining technology is applied to the selection of the students of the Informatics Olympiad. The results of mining can promote the healthy development of Osei. This paper takes the questionnaire for the participants in Informatics as the data sample. The improved Apriori algorithm is applied to the selection of the students of the Informatics Olympiad. The main contents include: 1.Discusses the main idea and execution process of the Apriori algorithm, 2. An improved algorithm Tire-Apriori. the basic idea of the improved algorithm based on dictionary tree and transaction projection is introduced. The theoretical basis and the implementation steps of the algorithm are analyzed in detail with an example. C language is used to program the algorithm, and the advantage of Tire-Apriori algorithm is verified by experiments. 3. Tire-Apriori is used to select the students of the Informatics Olympiad. Taking the questionnaire designed in this paper as the data source, the process of data acquisition and preprocessing is analyzed. This paper uses Tire-Apriorii to mine the data in two situations: first, mining the relationship between the award and the students' characteristics, which provides the criteria for the selection of the coach of the Olympiad of Informatics. Explore the relationship between the Olympiad of Informatics and quality Education and attract more students who have the ability to participate in the competition to participate in the competition team voluntarily.
【学位授予单位】:华侨大学
【学位级别】:硕士
【学位授予年份】:2015
【分类号】:TP311.13
【参考文献】
相关期刊论文 前2条
1 李婷;傅钢善;;国内外教育数据挖掘研究现状及趋势分析[J];现代教育技术;2010年10期
2 刘学才;;数学建模中的知识发现与数据挖掘[J];中国科技信息;2006年21期
相关硕士学位论文 前1条
1 徐宁;高中数学学习过程中的性别差异性研究[D];上海师范大学;2011年
,本文编号:1514935
本文链接:https://www.wllwen.com/guanlilunwen/yingxiaoguanlilunwen/1514935.html