论数据发掘的计算智能方法

On Computational Intelligence Approaches to Data Mining

一、数据发掘：从戮据库发现知识 随着现代科学技术的迅速发展,数据库的规模日益扩大,人们需菱有新的、更为有效的手段对各种“数据矿藏”(信息资源)进行开采以发挥其应用潜。数据发掘与 KDD正是在这样的应用需求背景下产生并迅速发展起来的、开发信息资源的一整套科学方法、算注及软件工具与环境。

A general survey on the issues of data mining (DM) and knowledge discovery in databases (KDD) is given first. The machine learning is emphasized as the nature of data mining as KDD. The differences as well as association of DM with respect to on-line analysis processing (OLAP) are discussed. It follows a concise discussion of the essentials of the computational intelligence (CI),characteristics of CI-algorithms as a way of machine learning,and so on. The potentialities and perspectives of it' s applications are also discussed with a typical case-study: discovering the prediction model of financial market price fluctuation lie hidden in the chaos of the specific data nuggets.