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On stabbing queries for generalized longest repeat

机译:刺刺查询中的最长最长重复

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A longest repeat query on a string, motivated by its applications in many subfields including computational biology, asks for the longest repetitive substring(s) covering a particular string position (point query). In this paper, we extend the longest repeat query from point query to interval query, allowing the search for longest repeat(s) covering any position interval, and thus significantly improve the usability of the solution. Our method for interval query takes a different approach using the insight from a recent work on shortest unique substrings [1], as the prior work's approach for point query becomes infeasible in the setting of interval query. Using the critical insight from [1], we propose an indexing structure, which can be constructed in the optimal O(n) time and space for a string of size n, such that any future interval query can be answered in O(1) time. Further, our solution can find all longest repeats covering any given interval using optimal O(occ) time, where occ is the number of longest repeats covering that given interval, whereas the prior O(n)-time and space work can find only one candidate for each point query. Experiments with real-world biological data show that our proposal is competitive with prior works, both time and space wise, while providing with the new functionality of interval queries as opposed to point queries provided by prior works.
机译:对字符串的最长重复查询是由其在包括计算生物学在内的许多子领域中的应用所激发的,要求最长的重复子字符串覆盖特定的字符串位置(点查询)。在本文中,我们将最长的重复查询从点查询扩展到间隔查询,从而允许搜索覆盖任何位置间隔的最长重复,从而显着提高了解决方案的可用性。我们的区间查询方法采用了最近研究中关于最短唯一子串的见解的另一种方法[1],因为先前的点查询方法在区间查询的设置中变得不可行。利用来自[1]的批判性见识,我们提出了一种索引结构,该索引结构可以在大小为n的字符串的最佳O(n)时间和空间中构建,以便可以在O(1)中回答任何将来的间隔查询时间。此外,我们的解决方案可以使用最佳O(occ)时间找到覆盖任何给定间隔的所有最长重复,其中occ是覆盖该给定间隔的最长重复的数量,而先前的O(n)-时间和空间工作只能找到一个每个点查询的候选对象。对现实世界生物数据的实验表明,我们的建议在时间和空间上都与先前的研究具有竞争性,同时提供了间隔查询的新功能,而不是先前的研究提供的点查询。

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