数据开采机模型及开采算法研究

Research on the Model of Data Mining and the Data Mining Algorithms

本文在介绍数据开采基本知识的基础上提出了一个通用的开采机模型 ,并对其各模块的功能做出描述 .针对目前许多开采大型数据库中的关联规则高效算法大多是在各自单独的领域内进行算法的理论研究与探讨的问题 ,本文在研究了两种高效的关联规则开采算法 :最大频繁项目集发现算法 FID(Frequent Item sets Discovery) ,增量式更新算法IU A(Incremental Updating Algorithm)后 ,将以上算法综合并在计算机上实现 ,作为比较同时给出了 Aprioiri(经典的关联规则开采算法 )的实现 .文中为了避免负面示例的影响 ,还引入了兴趣度的概念 ,并在系统中实现 .

Based on the basic knowledge of dada mining, this paper presents a common model for data mining and describes its module function. There have been many algorithms proposed for efficient discovery of association rules in large database, but most of them are described separately on their own fields. Base on the researching of two efficient algorithms: one algorithm is used to find the largest frequent itemsets(FID), the other is an incremental updating algorithm(IUA),this paper combines two algorithms and implement it. In addition, in order to avoid the misleading of potential negative examples, this paper presents interest value and defines it in form.