《Apriori算法优化及其在挖掘学生成绩中的应用》-毕业论文.doc

哈尔滨工业大学工学硕士学位论文 PAGE 10 - - w 摘要 随着数据库技术的发展，人们采集数据的能力越来越高，信息快速膨胀，人们急需从这些数据中得到有用的知识，于是数据挖掘技术应运而生。数据挖掘的过程即是从大量的数据中获取有趣知识的过程，而关联规则作为它的一个重要分支，更是为决策过程提供良好的手段。本文则是围绕着这一关联规则这一主题进行探索。首先简单介绍了关联规则的定义、分类、挖掘过程，然后着重介绍了挖掘模型Apriori算法，并提出了一种基于事务压缩的改进算法，最后针对我们信管专业同学的成绩这一成绩作为原始数据，在SPSS Clementine 这一挖掘平台上进行关联规则的挖掘，以获取不同课程学习之间的一些关系。 关键词　数据挖掘 关联规则 Apriori算法 SPSS Clementine Abstract With the development of database technology, the capacity for data collection has advanced more and more quickly, inducing the rapid expansion of information, Data mining techniques emerged for people need to get interesting knowledge from these data. Data mining process is to obtain interesting knowledge from a large number of data. Association rules as an important branch of it, is to provide a good means of decision-making process. This article is centered on the theme of this association rules. First, a brief definition of association rules, classification and data mining process, and then focuses on the mining model Apriori algorithm, and proposes a transaction-based compression of the improved algorithm, and finally fuses our students’scores as the original data, making data mining about association rule on the mining plat SPSS Clementine, to obtain a number of different relationships between courses. Keywords Data Mining association Apriori SPSS Clementine 目录 目录 TOC \o 1-3 \h \z \u HYPERLINK \l _Toc260840418 摘要 PAGEREF _Toc260840418 \h I HYPERLINK \l _Toc260840419 Abstract PAGEREF _Toc260840419 \h I HYPERLINK \l _Toc260840420 第1章 绪论 PAGEREF _Toc260840420 \h 3 HYPERLINK \l _Toc260840421 1.1 课题背景 PAGEREF _Toc260840421 \h 3 HYPERLINK \l _Toc260840422 1.1.1 学术背景 PAGEREF _Toc260840422 \h 3 HYPERLINK \l _Toc260840423 1.1.2 商业背景 PAGEREF _Toc260840423 \h 3 HYPERLINK \l _Toc260840424 1.2 研究内容 PAGEREF _Toc260840424 \h 4 HYPERLINK \l _Toc260840425 第2章 关联规则 PAGEREF _Toc260840425 \h 5 HYPERLINK \l _Toc260840426 2.1 基本概念 PAGEREF _Toc260840426 \h 5 HYPERLINK \l _Toc260840427 2.1.1 定义 PAG