【作者】 王雪岩；

【导师】 俞经善；

【作者基本信息】 哈尔滨工程大学 ， 计算机应用技术， 2006， 硕士

【摘要】 数据挖掘是近年来迅速发展的信息处理技术。数据挖掘就是从大量的、不完全的、有噪声的、模糊的、随机的数据中，提取隐含在其中的、人们事先不知道的、但又是潜在有用的信息和知识的过程。 关联规则挖掘作为数据挖掘领域的一个重要研究分支，它的任务是发现所有满足支持度阈值和置信度阈值的强关联规则。近年来，关联规则挖掘研究已经成为数据挖掘中的一个热点，并被广泛应用于市场营销、事务分析等应用领域。关联规则挖掘算法是关联规则挖掘研究的主要内容，迄今为止已提出了许多高效的关联规则挖掘算法。 本文首先对数据挖掘作了一般性讨论，包括数据挖掘的概念、任务、模式以及数据挖掘的应用和发展趋势。然后，本文对关联规则挖掘算法做了深入地研究，分析了关联规则挖掘中经典的Apriori算法及其他学者对Apriori算法的改进技术，并总结了Apriori算法中存在的问题。本文基于Apriori算法，提出了一种更高效的关联规则挖掘算法，在扫描数据库的同时把支持每个项目的事务都标记出来，采用一种新的方法来生成候选项目集，该算法只需对源数据库进行一次扫描就可以找出所有的频繁集，具有很高的效率。更多还原

【Abstract】 Data Mining is an information processing technology, which is developing very fast in recent years. Using data mining, people can abstract information and knowledge from a great deal of data which is incomplete, noisy, dark and random.The information and knowledge we got was ignored and had not been known before but potentially useful.Association rule mining is an important sub-branch of the Data Mining, which mines interesting association or correlation relationships among a large set of data items. Association rules are considered interesting if they satisfy both a minimum support threshold and a minimum confidence threshold. Association rule mining has become a hot research topic in recent years, and it has been used widely in selective marketing, decision analysis and business management. Association rule mining algorithms are the core contents in the area. So far, there are several famous typical algorithms.Firstly, this paper generally discusses the Data Mining, including the concepts and the pattern of the Data Mining, the application and development trend of the Data Mining. Secondly, this thesis deeply researches the association rule mining algorithm, which is important in the Data Mining. It analyses Apriori algorithm, which is classic in the association rule mining algorithms, and the improved technology of Apriori algorithm, and summarizes problems existing in Apriori algorithm. Based on Apriori algorithm, this paper presents a more efficient algorithm for association rule mining. The new algorithm adopts a unique way to generate the candidate itemsets. This is a high efficient algorithm which can mine all the frequent itemsets by scanning the source database only once.更多还原