Study on Mining Association Rules from Stock Time Series Data

被引：0

作者：

Xian, Tan ^{[1
]}

机构：

[1] Hubei Univ Nationalities, Enshi, Hubei Province, Peoples R China

来源：

SENSORS, MEASUREMENT AND INTELLIGENT MATERIALS, PTS 1-4 | 2013年 / 303-306卷

关键词：

Time Series; Association Rules Mining; Sequential pattern mining; Soft Computing;

D O I：

10.4028/www.scientific.net/AMM.303-306.1119

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Rough set theory is a kind of ambiguity and imprecision new mathematical tools, using precise mathematical analysis of imprecise system an ideal method. Rough set theory has powerful data reduction capability, this paper rough set theory to model the stock time series data, reduction, rule extraction, study the ups and downs of the relationship between the stock price, the use of advanced data mining techniques to dig out price linkage between stock association rules, has a very important significance.

引用

页码：1119 / 1124

页数：6