Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (14): 135-137.DOI: 10.3778/j.issn.1002-8331.2010.14.040
• 数据库、信号与信息处理 • Previous Articles Next Articles
ZHANG Zhong-lin,LIU Jun,XIE Yan-feng
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张忠林,刘 俊,谢彦峰
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Abstract: According to the characteristics of the rules change over time,it establishes the change trend analysis and forecasting model about support and confidence of the meta-association rule.By increasing the support and confidence vector evaluation of the rules,it gives the dynamic association rules of Meta-association formal definition.Using auto-regression Markov model of mining dynamic association rules of meta-association rules,it proves the effectiveness of this method.
Key words: dynamic association rule, meta-association rule mining, auto-regression model, Markov chains
摘要: 针对规则随着时间变化的特点,为规则建立元规则对其支持度和置信度变化趋势的分析和预测模型。通过增加支持度向量和置信度向量这两种规则评价指标,给出了动态关联规则元规则的形式化定义。利用自回归Markov模型对动态关联规则的元规则进行了挖掘,并通过实例证明了该方法的有效性。
关键词: 动态关联规则, 元规则挖掘, 自回归模型, Markov链
CLC Number:
TP391
ZHANG Zhong-lin,LIU Jun,XIE Yan-feng. Auto-regression Markov model application in mining of dynamic association rule[J]. Computer Engineering and Applications, 2010, 46(14): 135-137.
张忠林,刘 俊,谢彦峰. AR-Markov模型在动态关联规则挖掘中的应用[J]. 计算机工程与应用, 2010, 46(14): 135-137.
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URL: http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.2010.14.040
http://cea.ceaj.org/EN/Y2010/V46/I14/135