Suppose we are asked to index a text $T [0..n - 1]$ such that, given a pattern $P [0..m - 1]$, we can quickly report the maximal substrings of $P$ that each occur in $T$ at least $k$ times. We first show how we can add $O (r \log n)$ bits to Rossi et al.'s recent MONI index, where $r$ is the number of runs in the Burrows-Wheeler Transform of $T$, such that it supports such queries in $O (k m \log n)$ time. We then show how, if we are given $k$ at construction time, we can reduce the query time to $O (m \log n)$.
翻译:假设我们被要求将一个文本[0.n - 1] 指数化,这样,鉴于一个模式[0.m - 1]美元,我们可以迅速报告每个文本以美元为单位的最大子字符串($P)至少以美元为单位,每份以美元为单位,每份以美元为单位,每份以美元为单位。我们首先展示我们如何将O(r\log n)元(r\log n)元(美元)加到Rossi等人最近的MONI指数中,其中美元是Burrows-Wheeler变换中以美元为单位的运行量($T),因此它支持这种查询的时间为$O(km\log n)美元(k m)。然后我们展示,如果我们在施工时得到美元,我们如何将查询时间减到$O(m\log n美元)。