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包括论文,设计,论文字数:13528,页数:31
摘 要
随着信息时代的发展，信息量呈几何级数增长，人们发现从这些海量信息中获取有用的信息越来越困难，要找出信息背后隐藏的规律更是不可想象。数据挖掘就是从大量数据中获取有用信息的一门新技术，关联规则挖掘是数据挖掘方法中的一种。本文详细论述了基于Apriori算法的关联规则挖掘系统的设计开发过程。系统基于经典的Apriori算法，对事务数据库进行了位图矩阵转换，大大提高了搜索效率，并能分别挖掘频繁项集和关联规则。
论文组织如下：首先介绍了数据挖掘的产生、定义和应用；接着阐述了关联规则挖掘的基本概念；然后对系统的需求进行了分析，并提出设计方案；紧接着是系统的具体实现；最后对系统进行了测试，将系统用于挖掘中药方剂库中的药对药组，验证了系统的正确性和实用性。
关键词：数据挖掘；关联规则；Apriori算法The Design and Implementation of Association Rules Mining System based on Apriori Arithmetic
Abstract
With the development of the information era, the quantity of information increases in the way of geometric series, and people find that it is more and more difficult to obtain valuable informatin and it is incogitable to find out the rules hiding in the information. Data mining is a new technology to mine valuable informatin from abundant data, and association rules mining is a method of data mining. This paper elaborates on the process of the design and development of association rules mining system based on Apriori . The system is based upon classical Apriori arithmetic, and converts chinese medicine prescriptions database to a bitmap matrix, which greatly enhances the efficiency of search, and can mine frequent items and association rules respectively.
The paper is organized as following: Firstly, introduces the generation, definition and application of data mining; Secondly, sets forth the conception of association rules mining; Thirdly, analyzes the demand of the system, and propses the design project and implements the system; Finally, gives a test to mine chinese medicine groups from a chinese medicine prescriptions data, which proves the system valid and applicable.
Key words: Data mining; Apriori; Chinese traditional medicine
目录
1引言 1
2数据挖掘概述 1
2.1数据挖掘的产生 1
2.2数据挖掘的定义 1
2.3 数据挖掘的应用 4
3关联规则挖掘 4
3.1基本概念 4
3.2购物篮分析 5
3.3Apriori经典算法 6
4需求分析和设计方案 8
4.1需求分析 8
4.2设计方案 8
5基于Apriori算法的关联规则挖掘系统 10
5.1数据挖掘在中药方剂研究中的应用 10
5.2基于Apriori算法的关联规则挖掘系统的实现 11
5.2.1连接数据库 11
5.2.2位图矩阵的建立 11
5.2.3频繁项集 13
5.2.4关联规则 14
6系统测试 19
6.1系统的使用 19
6.2对显示数据的解释 22
6.3分析 23
结 论 24
参考文献 24
致 谢 26
声 明 27
