浅谈数据挖掘理论

数据挖掘(Database mining,DM),也常被称为数据库中的知识发现(Knowledge Discovery in Database,KDD),是从大量数据中提取出可信、新颖、有效并能被人理解的模式的高级处理过程。它由一些大型零售机构所面临的决策支持问题(Decision support problem)所激发,通过对数据进行挖掘,我们可以找到对商业销售及生产极为有效的一些信息,这些信息一般通过具体的模式得到反映。数据挖掘将是今后几年全球范围内重点投资研究的十大新技术之一,它引起了学术界和工业界的广泛关注,是当今数据库系统研究和应用领域内的一个热点问题。最后,本文简要介绍了数据挖掘其他特定的功能模式及其应用和发展,希望给读者一个数据挖掘发展的全貌。

DM （Database mining） , also called KDD （Knowledge Discovery in Database） usually, is an advanced process, in which we can pick up many trustful, novel, useful and readable patterns from very large amounts of data. It is motivated by the decision support problem faced by most large retail organizations. We can get some information useful for sale or produce procedure through mining in the data while the information usually reflected by a certain pattern. Database mining is one of the ten new technologies on which intensive research work worldwide will be focused in the several years to come. It receives much attention from both academic field and industrial field and becomes one of the hot topics in the research and application of data base system. At the end of this paper, it introduces other function modes of database mining, including their application and development in the near future, in the hope of giving the readers an all-sided comprehension about the database mining development.