MinMax: A new algorithm for maximal frequent pattern mining

被引：0
|
作者：
Wang, H [1 ]
Li, QH [1 ]
Jiang, SY [1 ]
Ma, CX [1 ]
机构：
[1] Huazhong Univ Sci & Technol, Comp Sch, Wuhan 430074, Peoples R China
来源：
7TH WORLD MULTICONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL VI, PROCEEDINGS: INFORMATION SYSTEMS, TECHNOLOGIES AND APPLICATIONS: I | 2003年
关键词：
maximal frequent pattern; pruning strategy and mining algorithm;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Frequent patterns play an essential role in many data mining tasks. The complexity of the problem has been shown as NP-hard. Pruning strategies are widely used to improve the efficiency of mining algorithms. It has been observed that the search efficiency cannot be improved by using these strategies even together, where unnecessary redundant nodes are still explored. We present a novel and powerful algorithm for mining maximal frequent patterns, called MinMax. An optimal and multiple level backtrack pruning is proposed. The analysis and experimental results demonstrate the superb efficiency of our approach in comparison with the previous work.
引用
收藏
页码：19 / 21
页数：3
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