摘要
股票交易各业务系统积累了大量数据。对这些数据进行有效的分析处理,以发现在股票交易数据间的内在相互联系,对指导投资决策具有重要的意义。文中针对股票交易建立了一种分析模型,并给出该模型的数据预处理算法。在此基础上,通过采用关联规则挖掘的思想实现该类规则的挖掘算法,实验证明该模型和算法是有效的。
The security companies in stocks transactions have accumulated a large number of data. It is very important to making decision for investment to effectively use the data and find the interactional relation between the data. This paper constructs the model in stocks transactions and gives the data pre-process algorithms and implements the mining algorithm of such rules. The model and algorithm are proved to be efficient by experiment and helpful to investment.
出处
《微机发展》
2005年第9期152-153,157,共3页
Microcomputer Development
关键词
关联规则
股票分析
序列模式
assoeiation rules
stock analysis
sequential rule
