The edit distance to k-subsequence universality

IF 1.1 3区 计算机科学 Q1 BUSINESS, FINANCE
Joel D. Day , Pamela Fleischmann , Maria Kosche , Tore Koß , Florin Manea , Stefan Siemer
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引用次数: 0

Abstract

A word u is a subsequence of another word w if u is obtained from w by deleting some of its letters. In the 1970s, Simon defined the relation k (called now Simon-Congruence) as follows: two words having the same set of subsequences of length k are k-congruent. It is thus natural to ask, for non k-equivalent words w and u, what is the minimal number of edit operations that we need to perform on w to obtain a word which is k-equivalent to u. Here, we consider this problem in a specific setting: when u is a k-subsequence universal word. A word u with alph(u)=Σ is called k-subsequence universal if the set of length-k subsequences of u contains all possible words of length k over Σ. As such, our results are a series of efficient algorithms computing the edit distance from w to the language of k-subsequence universal words.
对k-子序列通用性的编辑距离
一个单词u是另一个单词w的子序列,如果u是通过删除w中的一些字母而得到的。在20世纪70年代,Simon定义了关系~ k(现在称为Simon-同余)如下:具有相同长度为k的子序列集的两个单词是~ k同余的。因此,很自然地要问,对于非k-等价的单词w和u,我们需要对w执行多少次编辑操作才能获得一个与u - k-等价的单词。这里,我们在一个特定的设置中考虑这个问题:当u是一个k-子序列全称词时。如果u的长度为k- k的子序列集合包含了长度为k / Σ的所有可能的单词,那么一个单词u (u)=Σ被称为k-子序列全称。因此,我们的结果是一系列有效的算法,计算从w到k-子序列通用词的语言的编辑距离。
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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来源期刊
Journal of Computer and System Sciences
Journal of Computer and System Sciences 工程技术-计算机:理论方法
CiteScore
3.70
自引率
0.00%
发文量
58
审稿时长
68 days
期刊介绍: The Journal of Computer and System Sciences publishes original research papers in computer science and related subjects in system science, with attention to the relevant mathematical theory. Applications-oriented papers may also be accepted and they are expected to contain deep analytic evaluation of the proposed solutions. Research areas include traditional subjects such as: • Theory of algorithms and computability • Formal languages • Automata theory Contemporary subjects such as: • Complexity theory • Algorithmic Complexity • Parallel & distributed computing • Computer networks • Neural networks • Computational learning theory • Database theory & practice • Computer modeling of complex systems • Security and Privacy.
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