Approximate string searching with fast fourier transforms and simplexes

Daniel Liu
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引用次数: 1

Abstract

Previous algorithms for solving the approximate string matching with Hamming distance problem with wildcard ("don't care") characters have been shown to take \(O(|\Sigma| N \log M)\) time, where \(N\) is the length of the text, \(M\) is the length of the pattern, and \(|\Sigma|\) is the size of the alphabet. They make use of the Fast Fourier Transform for efficiently calculating convolutions. We describe a novel approach of the problem, which makes use of special encoding schemes that depend on \((|\Sigma| - 1)\)-simplexes in \((|\Sigma| - 1)\)-dimensional space.
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近似字符串搜索与快速傅里叶变换和简单
先前用于解决带有通配符(“不关心”)字符的近似字符串匹配与汉明距离问题的算法已被证明需要\(O(|\Sigma| N \log M)\)时间,其中\(N\)是文本的长度,\(M\)是模式的长度,\(|\Sigma|\)是字母表的大小。他们利用快速傅里叶变换来有效地计算卷积。我们描述了一种解决该问题的新方法,该方法利用了在\((|\Sigma| - 1)\)维空间中依赖于\((|\Sigma| - 1)\) -simplexes的特殊编码方案。
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