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一种关联规则增量式挖掘算法研究 被引量：2

An algorithm of associative rule increment mining
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摘要 现有关联规则更新算法都是基于支持度-置信度框架而提出的,仅针对大于最小支持度闭值的频繁项集进行挖掘。为了提高告警关联规则的完整性和准确性,在相关度AARSC算法基础上,提出了一种增量式挖掘UAARSC算法(Updating-AARSC)。该算法对增量计算进行了改进,可以发现频繁和非频繁告警序列间的关联规则。 The existing algorithms of association rule update are based on the framework of support-confidence and they mine only the frequent closure of the set value greater than the minimum support. To enhance the completeness and accuracy, the author presents in this paper an increment mining UAARSC algorithm based On the correlative AARSC algorithm. The algorithm improves incremental computation and may find the associative rules between the frequent and non-frequent alarm sequences.
作者 刘造新
机构地区 江西交通职业技术学院信息工程系
出处 《计算机时代》 2012年第3期20-21,24,共3页 Computer Era
关键词 关联规则 数据发掘 滑动窗口 增量计算 associative rules data mining sliding window incremental computation
分类号 TP3 [自动化与计算机技术—计算机科学与技术]
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参考文献6

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共引文献226

同被引文献15

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  • 7GRECO S, SLOWHqSKI R, SZCZECH I. Properties of rule interestingness measures and alternative approaches to normalization of measures, Information Sciences, Volume 216, 20 December 2012, Pages 1-16, ISSN 0020-0255, 10.1016/j.ins.2012.05.018.
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计算机时代
2012年 第3期

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