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微阵列数据中Top-k频繁闭合项集挖掘
引用本文:史建军,缪裕青.微阵列数据中Top-k频繁闭合项集挖掘[J].计算机工程,2011,37(2):60-62.
作者姓名:史建军  缪裕青
作者单位:1. 桂林电子科技大学计算机与控制学院,广西,桂林,541004
2. 桂林电子科技大学计算机与控制学院,广西,桂林,541004;阿德莱德大学计算机科学学院,南澳大利亚,5005
摘    要:现有大部分微阵列数据中频繁闭合项集的挖掘需要事先给定最小支持度,但在实际应用中该最小支持度很难确定。针对该问题,提出top-k频繁闭合项集挖掘算法,基于自顶向下宽度优先搜索策略挖掘项集长度不小于min_l的top-k频繁闭合项集,并对搜索空间进行有效修剪,从而提高搜索速度。实验结果表明,该算法的时间性能在多数情况下优于CARPENTER算法。

关 键 词:微阵列数据  top-k频繁闭合项集  自顶向下  宽度优先

Top-k Frequent Closed Item Set Mining in Microarray Data
SHI Jian-jun,MIAO Yu-qing.Top-k Frequent Closed Item Set Mining in Microarray Data[J].Computer Engineering,2011,37(2):60-62.
Authors:SHI Jian-jun  MIAO Yu-qing
Affiliation:SHI Jian-jun1,MIAO Yu-qing1,2(1.School of Computer and Control,Guilin University of Electronic Technology,Guilin 541004,China,2.School of Computer Science,The University of Adelaide,South Australia 5005,Australia)
Abstract:Most previous mining frequent closed item sets require the specification of a minimum support threshold in microarry data.However,it is difficult for users to provide an appropriate minimum support threshold in practice.Aiming at this problem,this paper presents a top-k frequent closed item set and an algorithm in microarray data.The algorithm uses top-down breadth-first search strategy to mining top-k frequent closed item set of length no less than given value min_l and pruning the search space effectively...
Keywords:microarray data  top-k frequent closed item set  top-down  breadth-first  
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