股票交易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。本文在经典Apriori算法的基础上,提出了一种考虑时间因素的关联规则挖掘算法,将其应用于股票市场,对各支股票间的关联规则进行了有效的挖掘和探讨,提高了挖掘过程的效率。
The security companies accumulats a large number of datas,which is very imporant to make effective decision for investmenters.This paper presents an association rule algorithm based on traditional Apriori.This algorithm adds on consideration on time influence and apply it in stocks,produces good results.