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An In-place Framework for Exact and Approximate Shortest Unique Substring Queries

机译:用于精确和近似最短的独特子字符串查询的就地框架

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We revisit the exact shortest unique substring (SUS) finding problem, and propose its approximate version where mismatches are allowed, due to its applications in subfields such as computational biology. We design a generic in-place framework that fits to solve both the exact and approximate k-mismatch SUS finding, using the minimum 2n memory words plus n bytes space, where n is the input string size. By using the in-place framework, we can find the exact and approximate k-mismatch SUS for every string position using a total of O(n) and O(n~2) time, respectively, regardless of the value of k. Our framework does not involve any compressed or succinct data structures and thus is practical and easy to implement.
机译:我们重新审视了确切的最短独特子字符串(SUS)发现问题,并提出了其允许不匹配的近似版本,因为它在诸如计算生物学的子场中的应用。我们设计了一种通用的就地框架,适合使用最小2N内存单词加n个字节空间来解决精确和近似的k-mismatch sus查找,其中n是输入字符串大小。通过使用就地框架,我们可以分别找到每个弦位置的精确和近似的k-mismatch sus,使用总共O(n)和o(n〜2)时间,无论k的值如何。我们的框架不涉及任何压缩或简洁的数据结构,因此实用且易于实现。

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