Apriori 数据挖掘算法的C#实现

数据库中的知识发现 (Knowledge Discovery in Databases,KDD) 是利用计算机自动地从海量信息中提取有用的知识 , 是一种有效利用信息的新方法 , 目前已成为数据库领域的研究热点之一。 KDD 的研究焦点在于数据挖掘。数据挖掘是从大型数据库或数据仓库中提取人们感兴趣的知识 , 这些知识是隐含的 , 事先未知的潜在的有用信息。主要包括的方法有 : 分类、回归分析、聚类、关联分析等 [1][5] 。关联规则的提取主要针对大型事务数据库。由于关联规则提取需要重复扫描数据库 , 因而提高算法的效率是至关重要的。

-Apriori data mining algorithms C# knowledge discovery in databases (Knowledge Discovery in Databases, KDD) is using the computer to automatically extract useful knowledge from the mass of information is an effective use of the new method of information has become the database field research focus. KDD research focuses on data mining. Data mining is extracted from a large database or data warehouse people are interested in knowledge, such knowledge is implicit, previously unknown potentially useful information. Mainly include: classification, regression analysis, clustering, association analysis [1] [5]. The extraction of association rules mainly for large transaction database. Association rules extraction need to repeat the scan database, and therefore it is essential to improve the efficiency of the algorithm.