Parameterized Algorithms for String Matching to DAGs: Funnels and Beyond

Manuel Cáceres
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引用次数: 3

Abstract

The problem of String Matching to Labeled Graphs (SMLG) asks to find all the paths in a labeled graph $G = (V, E)$ whose spellings match that of an input string $S \in \Sigma^m$. SMLG can be solved in quadratic $O(m|E|)$ time [Amir et al., JALG], which was proven to be optimal by a recent lower bound conditioned on SETH [Equi et al., ICALP 2019]. The lower bound states that no strongly subquadratic time algorithm exists, even if restricted to directed acyclic graphs (DAGs). In this work we present the first parameterized algorithms for SMLG in DAGs. Our parameters capture the topological structure of $G$. All our results are derived from a generalization of the Knuth-Morris-Pratt algorithm [Park and Kim, CPM 1995] optimized to work in time proportional to the number of prefix-incomparable matches. To obtain the parameterization in the topological structure of $G$, we first study a special class of DAGs called funnels [Millani et al., JCO] and generalize them to $k$-funnels and the class $ST_k$. We present several novel characterizations and algorithmic contributions on both funnels and their generalizations.
字符串与dag匹配的参数化算法:漏斗及其他
标记图的字符串匹配问题(SMLG)要求在标记图$G = (V, E)$中找到所有的路径,其拼写与输入字符串$S \in \Sigma^m$匹配。SMLG可以在二次$O(m|E|)$ time中求解[Amir等人,JALG],最近在SETH条件下的下界证明了它是最优的[Equi等人,ICALP 2019]。下界表明不存在强次二次时间算法,即使局限于有向无环图(dag)。在这项工作中,我们提出了在dag中SMLG的第一个参数化算法。我们的参数捕获了$G$的拓扑结构。我们所有的结果都来自于Knuth-Morris-Pratt算法的推广[Park和Kim, CPM 1995],优化后的算法与前缀不可比较匹配的数量成正比。为了获得$G$拓扑结构中的参数化,我们首先研究了一类特殊的dag,称为漏斗[Millani et al., JCO],并将其推广到$k$-漏斗和$ST_k$类。我们提出了几个新的表征和算法贡献在这两个漏斗和他们的推广。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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