Mining frequent patterns from sequences

Jun-yan Zhang, Fan Min
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引用次数: 1

Abstract

Pattern mining is a popular issue in biological sequence analysis. In this paper, we propose new definitions related to the pattern frequency, where gaps are mined instead of specified. We develop algorithm with polynomial complexities. Patterns can grow from both sides, and Apriori property holds. Some interesting biological patterns are mined by our algorithm.
从序列中挖掘频繁模式
模式挖掘是生物序列分析中的一个热点问题。在本文中,我们提出了与模式频率相关的新定义,其中间隙被挖掘而不是指定。我们开发了具有多项式复杂度的算法。模式可以从两边生长,Apriori属性成立。我们的算法挖掘了一些有趣的生物模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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