Optimal LZ-End Parsing is Hard

H. Bannai, Mitsuru Funakoshi, Kazuhiro Kurita, Yuto Nakashima, Kazuhisa Seto, T. Uno
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引用次数: 0

Abstract

LZ-End is a variant of the well-known Lempel-Ziv parsing family such that each phrase of the parsing has a previous occurrence, with the additional constraint that the previous occurrence must end at the end of a previous phrase. LZ-End was initially proposed as a greedy parsing, where each phrase is determined greedily from left to right, as the longest factor that satisfies the above constraint~[Kreft&Navarro, 2010]. In this work, we consider an optimal LZ-End parsing that has the minimum number of phrases in such parsings. We show that a decision version of computing the optimal LZ-End parsing is NP-complete by showing a reduction from the vertex cover problem. Moreover, we give a MAX-SAT formulation for the optimal LZ-End parsing adapting an approach for computing various NP-hard repetitiveness measures recently presented by [Bannai et al., 2022]. We also consider the approximation ratio of the size of greedy LZ-End parsing to the size of the optimal LZ-End parsing, and give a lower bound of the ratio which asymptotically approaches $2$.
最佳LZ-End解析是困难的
LZ-End是著名的Lempel-Ziv解析家族的一种变体,这样,解析的每个短语都有一个先前的事件,并且附加了一个约束,即先前的事件必须在前一个短语的末尾结束。LZ-End最初被提出为贪婪解析,其中每个短语从左到右贪婪地确定,作为满足上述约束的最长因子~[Kreft&Navarro, 2010]。在这项工作中,我们考虑了一种最优的LZ-End解析,它在这种解析中具有最少数量的短语。通过展示顶点覆盖问题的约简,我们证明了计算最优LZ-End解析的决策版本是np完全的。此外,我们给出了最佳LZ-End解析的MAX-SAT公式,该公式采用了最近由[Bannai等人,2022]提出的计算各种NP-hard重复度量的方法。我们还考虑了贪婪LZ-End解析的大小与最优LZ-End解析的大小的近似比值,并给出了该比值的下界,该比值渐近于$2$。
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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