Faster STR-IC-LCS computation via RLE

Keita Kuboi, Yuta Fujishige, Shunsuke Inenaga, H. Bannai, M. Takeda
{"title":"Faster STR-IC-LCS computation via RLE","authors":"Keita Kuboi, Yuta Fujishige, Shunsuke Inenaga, H. Bannai, M. Takeda","doi":"10.4230/LIPIcs.CPM.2017.20","DOIUrl":null,"url":null,"abstract":"The constrained LCS problem asks one to find a longest common subsequence of two input strings $A$ and $B$ with some constraints. The STR-IC-LCS problem is a variant of the constrained LCS problem, where the solution must include a given constraint string $C$ as a substring. Given two strings $A$ and $B$ of respective lengths $M$ and $N$, and a constraint string $C$ of length at most $\\min\\{M, N\\}$, the best known algorithm for the STR-IC-LCS problem, proposed by Deorowicz~({\\em Inf. Process. Lett.}, 11:423--426, 2012), runs in $O(MN)$ time. In this work, we present an $O(mN + nM)$-time solution to the STR-IC-LCS problem, where $m$ and $n$ denote the sizes of the run-length encodings of $A$ and $B$, respectively. Since $m \\leq M$ and $n \\leq N$ always hold, our algorithm is always as fast as Deorowicz's algorithm, and is faster when input strings are compressible via RLE.","PeriodicalId":236737,"journal":{"name":"Annual Symposium on Combinatorial Pattern Matching","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual Symposium on Combinatorial Pattern Matching","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4230/LIPIcs.CPM.2017.20","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

Abstract

The constrained LCS problem asks one to find a longest common subsequence of two input strings $A$ and $B$ with some constraints. The STR-IC-LCS problem is a variant of the constrained LCS problem, where the solution must include a given constraint string $C$ as a substring. Given two strings $A$ and $B$ of respective lengths $M$ and $N$, and a constraint string $C$ of length at most $\min\{M, N\}$, the best known algorithm for the STR-IC-LCS problem, proposed by Deorowicz~({\em Inf. Process. Lett.}, 11:423--426, 2012), runs in $O(MN)$ time. In this work, we present an $O(mN + nM)$-time solution to the STR-IC-LCS problem, where $m$ and $n$ denote the sizes of the run-length encodings of $A$ and $B$, respectively. Since $m \leq M$ and $n \leq N$ always hold, our algorithm is always as fast as Deorowicz's algorithm, and is faster when input strings are compressible via RLE.
更快的STR-IC-LCS计算通过RLE
约束LCS问题要求在一些约束条件下找到两个输入字符串$A$和$B$的最长公共子序列。STR-IC-LCS问题是约束LCS问题的一个变体,其中的解决方案必须包含一个给定的约束字符串$C$作为子字符串。给定长度分别为$M$和$N$的两个字符串$A$和$B$,以及长度不超过$\min\{M, N\}$的约束字符串$C$,由Deorowicz (Inf. {\emProcess)提出的STR-IC-LCS问题的最著名算法。左。}, 11:423—426,2012),运行时间为$O(MN)$。在这项工作中,我们提出了STR-IC-LCS问题的$O(mN + nM)$时间解决方案,其中$m$和$n$分别表示$A$和$B$的运行长度编码的大小。由于$m \leq M$和$n \leq N$总是成立,我们的算法总是和Deorowicz的算法一样快,并且当输入字符串通过RLE可压缩时更快。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信