基于树形结构的最新知识挖掘

Chun-Wei Lin, T. Hong, Wen-Hsiang Lu
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引用次数: 2

摘要

在过去,常用的模式是在频繁项集对应的生命周期内挖掘频繁项集。这种混合方法是基于类似apriori的方法,对计算量和内存的要求较高。本文提出了最新模式树(UDP树),将最新模式保存在树形结构中。实验结果表明,该方法具有较好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mining Up-to-Date Knowledge Based on Tree Structures
In the past, the up-to-date patterns is proposed to mine the frequent itemsets within its corresponding lifetime. This hybrid method is based on the Apriori-like approach, which requests high computational cost and memory requirement. In this paper, the up-to-date pattern tree (UDP tree) is proposed to keep the up-to-date patterns in a tree structure. The experimental results show that the proposed approach has a better performance than the level-wise up-to-date algorithm.
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