摘要：关联规则挖掘是发现已知数据中有趣的关系，属于数据挖掘方法之一。Apriori算法是Agrawal等人提出的经典的简单布尔关联规则挖掘算法。本文针对小型超市部分数据，结合Apriori算法，目的是分析出顾客在购买某些商品的基础上购买另一些商品的倾向，生成的关联规可以用于指导决策。在对Apriori算法进行学习的基础上，用C#语言设计实现，结合SQL数据库，并用图形界面将结果清晰的展现出来。算法实现过程中的设计思路、得到的结果和存在问题在文中给予了说明。另外，本文在功能基本实现的基础上，对数据有序化处理,从而使算法时间性能得到些许改进。

毕业论文关键词：关联规则，数据挖掘，Apriori算法，频繁集56359

Abstract：Association rule is one of the key technologies of data mining to find the funny association or relationship from the given dataset.Apriori algorithm is one of the most classic boolean，simple association rule data mining s which presented by Agrawal and etc.The paper is based on the small_and_partial supermarket’s transactions ,combined with Apriori algorithm ,so as to find the possibility of buying A and buying B at the same time .The regulation generated can be used in decision_making. After studied Apriori algorithm’s basic knowledge ,at the same time,designed and realized it in C# language combined with SQL database !Moreover ,the results will be clearly presented in windows .During the design period ,I have learned a lot about the Apriori algorithm ,the detailed design,results,and problems has been already noted in the paper .When simply realized the algorithm,I have made the data sequential trying optimize the algorithm in time_performance .

Key Words：association rule，data minging ,Apriori algorithm ,frequent item sets

目 录

1 绪论 3

1.1 Apriori算法 3

1.2 关联规则 4

1.3 数据挖掘 5

1.4 购物篮分析 5

2 算法设计与实现 5

2.1 算法设计与实现的开发环境 6

2.2 开发工具介绍 6

2.3 C#语言 6

3 关联规则概念详述 7

3.1 关联规则 7

3.2 项集 7

3.3 事务 7

3.4 支持度 7

3.5 置信度 8

3.6 强关联规则 8

4  Apriori算法详述 9

4.1 性质 9

4.2 寻找频繁项集的步骤 9

4.4 生成关联规则的步骤 10

4.5 生成关联规则的伪代码 10

4.6 算法实例描述 11

5 算法的设计与实现详述 12

5.1 算法实现流程图 12

5.2 数据库的设计 13

5.2 主界面的设计 15

5.3 产生频繁集的设计 16

5.5 产生关联规则的设计 18

5.6 Apriori算法的数据测试 21

5.7 算法数据的意义作用