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Improved algorithms for approximate string matching (extended abstract)

机译:改进近似字符串匹配的算法(扩展摘要)

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Background: The problem of approximate string matching is important in many different areas such as computational biology, text processing and pattern recognition. A great effort has been made to design efficient algorithms addressing several variantsof the problem, including comparison of two strings, approximate pattern identification in a string or calculation of the longest common subsequence that two strings share.Results: We designed an output sensitive algorithm solving the edit distance problem between two strings of lengths n and m respectively in time 0((s - |n - m|)min(m, n, s) + m + n) and linear space, where s is the edit distance between the two strings. This worst-case time bound sets the quadratic factor of the algorithm independentof the longest string length and improves existing theoretical bounds for this problem. The implementation of our algorithm also excels in practice, especially in cases where the two strings compared differ significantly in length.Conclusion: We have provided the design, analysis and implementation of a new algorithm for calculating the edit distance of two strings with both theoretical and practical implications. Source code of our algorithm is available online.
机译:背景:近似字符串匹配问题在许多不同的区域中是重要的,例如计算生物学,文本处理和模式识别。已经努力设计了解决问题的几个变体的高效算法,包括两个字符串的比较,在字符串中的近似模式识别或计算两个字符串共享的最长常见子项的计算值:我们设计了一个解决的输出敏感算法分别在时间0((S-| N - M |)min(m,n,s)+ m + n)和线性空间之间的两个长度n和m之间的距离问题,其中s是编辑距离之间的编辑距离两个字符串。这个最坏情况的时间绑定设置了算法的二次因素,独立于最长的字符串长度,并提高了此问题的现有理论界限。我们的算法的实施也在实践中擅长,特别是在两个字符串的长度上比较差异的情况下。结论:我们提供了一种新算法的设计,分析和实现,用于计算两个字符串的编辑距离与理论和理论实际影响。我们算法的源代码在线提供。

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