DryadeParent, An Efficient and Robust Closed Attribute Tree Mining Algorithm
DryadeParent, An Efficient and Robust Closed Attribute Tree Mining Algorithm
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DOI：
10.1109/tkde.2007.190695
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发表时间：
2008-03
影响因子：
8.9
通讯作者：
A. Termier;M. Rousset;M. Sebag;K. Ohara;T. Washio;H. Motoda
中科院分区：
文献类型：
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作者：
A. Termier;M. Rousset;M. Sebag;K. Ohara;T. Washio;H. Motoda
在本文中，我们提出了一种新的树挖掘算法，DryadeParent，基于 DRYADE 中首次引入的挂钩原理。在实验中，我们证明了要查找的频繁模式的分支因子和深度是树挖掘算法复杂性的关键因素，即使在以前的工作中经常被忽视。我们表明，在频繁树模式具有高分支因子的数据集上，DryadeParent 的性能比当前最快的算法 CMTreeMiner 好几个数量级。
In this paper, we present a new tree mining algorithm, DryadeParent, based on the hooking principle first introduced in DRYADE. In the experiments, we demonstrate that the branching factor and depth of the frequent patterns to find are key factors of complexity for tree mining algorithms, even if often overlooked in previous work. We show that DryadeParent outperforms the current fastest algorithm, CMTreeMiner, by orders of magnitude on data sets where the frequent tree patterns have a high branching factor.