We describe how, given a text $T [1..n]$ and a positive constant $\epsilon$, we can build a simple $O (z \log n)$-space index, where $z$ is the number of phrases in the LZ77 parse of $T$, such that later, given a pattern $P [1..m]$, in $O (m \log \log z + \mathrm{polylog} (m + z))$ time and with high probability we can find a substring of $P$ that occurs in $T$ and whose length is at least a $(1 - \epsilon)$-fraction of the length of a longest common substring of $P$ and $T$.

翻译：我们描述一下,如果文本为$T[1.n]美元,正值不变值为$epslon$,我们如何可以建立一个简单的美元(z\log n)美元-空间指数,其中z美元是77里拉的提法($T)中的短语数,因此以后,如果采用1P[1.m]美元的模式,则用美元(m\log\log z +\mathrm{polylog}(m + z)美元(m + z)时间和高概率,我们能找到一个以美元为单位,其长度至少是美元(1-\ epsilon)美元,其长度是美元和美元($)。