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相关论文: Space-efficient RLZ-to-LZ77 conversion

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We give algorithms that, given a straight-line program (SLP) with $g$ rules that generates (only) a text $T [1..n]$, builds within $O(g)$ space the Lempel-Ziv (LZ) parse of $T$ (of $z$ phrases) in time $O(n\log^2 n)$ or in time…

数据结构与算法 · 计算机科学 2023-10-11 Travis Gagie , Adrián Goga , Artur Jeż , Gonzalo Navarro

We present an algorithm that constructs the LZ-End parsing (a variation of LZ77) of a given string of length $n$ in $O(n\log\ell)$ expected time and $O(z + \ell)$ space, where $z$ is the number of phrases in the parsing and $\ell$ is the…

数据结构与算法 · 计算机科学 2020-12-15 Dominik Kempa , Dmitry Kosolobov

Lempel-Ziv (LZ77 or, briefly, LZ) is one of the most effective and widely-used compressors for repetitive texts. However, the existing efficient methods computing the exact LZ parsing have to use linear or close to linear space to index the…

数据结构与算法 · 计算机科学 2020-05-12 Dmitry Kosolobov , Daniel Valenzuela , Gonzalo Navarro , Simon J. Puglisi

We present a new algorithm for computing the Lempel-Ziv Factorization (LZ77) of a given string of length $N$ in linear time, that utilizes only $N\log N + O(1)$ bits of working space, i.e., a single integer array, for constant size integer…

数据结构与算法 · 计算机科学 2013-10-08 Keisuke Goto , Hideo Bannai

Given a positive \(\epsilon \leq 1\) and read-only access to a string \(S [1..n]\) whose LZ77 parse consists of $z$ phrases, with high probability we can build an LZ77-like parse of $S$ that consists of $\Oh{z / \epsilon}$ phrases using…

数据结构与算法 · 计算机科学 2015-03-10 Travis Gagie

We generalize Karp-Rabin string matching to handle multiple patterns in $\mathcal{O}(n \log n + m)$ time and $\mathcal{O}(s)$ space, where $n$ is the length of the text and $m$ is the total length of the $s$ patterns, returning correct…

数据结构与算法 · 计算机科学 2015-09-11 Johannes Fischer , Travis Gagie , Paweł Gawrychowski , Tomasz Kociumaka

The Lempel-Ziv parsing of a string (LZ77 for short) is one of the most important and widely-used algorithmic tools in data compression and string processing. We show that the Lempel-Ziv parsing of a string of length $n$ on an alphabet of…

数据结构与算法 · 计算机科学 2015-07-28 Djamal Belazzougui , Simon J. Puglisi

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…

数据结构与算法 · 计算机科学 2022-12-06 Nick Fagan , Jorge Hermo González , Travis Gagie

For both the Lempel Ziv 77- and 78-factorization we propose algorithms generating the respective factorization using $(1+\epsilon) n \lg n + O(n)$ bits (for any positive constant $\epsilon \le 1$) working space (including the space for the…

数据结构与算法 · 计算机科学 2015-04-13 Johannes Fischer , Tomohiro I , Dominik Köppl

Computing the LZ factorization (or LZ77 parsing) of a string is a computational bottleneck in many diverse applications, including data compression, text indexing, and pattern discovery. We describe new linear time LZ factorization…

数据结构与算法 · 计算机科学 2020-12-11 Juha Kärkkäinen , Dominik Kempa , Simon J. Puglisi

We introduce a new approach to LZ77 factorization that uses O(n/d) words of working space and O(dn) time for any d >= 1 (for polylogarithmic alphabet sizes). We also describe carefully engineered implementations of alternative approaches to…

数据结构与算法 · 计算机科学 2020-12-11 Juha Kärkkäinen , Dominik Kempa , Simon J. Puglisi

We propose a new approach for calculating the Lempel-Ziv factorization of a string, based on run length encoding (RLE). We present a conceptually simple off-line algorithm based on a variant of suffix arrays, as well as an on-line algorithm…

数据结构与算法 · 计算机科学 2015-03-20 Jun'ichi Yamamoto , Hideo Bannai , Shunsuke Inenaga , Masayuki Takeda

We show that both the Lempel Ziv 77- and the 78-factorization of a text of length $n$ on an integer alphabet of size $\sigma$ can be computed in $O(n \lg \lg \sigma)$ time (linear time if we allow randomization) using $O(n \lg \sigma)$ bits…

数据结构与算法 · 计算机科学 2016-05-31 Dominik Köppl , Kunihiko Sadakane

The Lempel-Ziv factorization (LZ77) and the Run-Length encoded Burrows-Wheeler Transform (RLBWT) are two important tools in text compression and indexing, being their sizes $z$ and $r$ closely related to the amount of text…

数据结构与算法 · 计算机科学 2017-02-07 Alberto Policriti , Nicola Prezza

Lempel-Ziv (LZ77) factorization is a fundamental problem in string processing: Greedily partition a given string $T$ from left to right into blocks (called phrases) so that each phrase is either the leftmost occurrence of a letter or the…

数据结构与算法 · 计算机科学 2025-06-19 Dominik Kempa , Tomasz Kociumaka

In this paper, we show that the LZ77 factorization of a text T {\in\Sigma^n} can be computed in O(R log n) bits of working space and O(n log R) time, R being the number of runs in the Burrows-Wheeler transform of T reversed. For extremely…

数据结构与算法 · 计算机科学 2015-10-22 Nicola Prezza , Alberto Policriti

Let $T [1..n]$ be a text over an alphabet of size $\sigma \in \mathrm{polylog} (n)$, let $r^*$ be the sum of the numbers of runs in the Burrows-Wheeler Transforms of $T$ and its reverse, and let $z$ be the number of phrases in the LZ77…

数据结构与算法 · 计算机科学 2025-08-19 Travis Gagie

The LZ-End parsing [Kreft & Navarro, 2011] of an input string yields compression competitive with the popular Lempel-Ziv 77 scheme, but also allows for efficient random access. Kempa and Kosolobov showed that the parsing can be computed in…

数据结构与算法 · 计算机科学 2024-09-18 Patrick Dinklage

We present a new, simple, and efficient approach for computing the Lempel-Ziv (LZ77) factorization of a string in linear time, based on suffix arrays. Computational experiments on various data sets show that our approach constantly…

数据结构与算法 · 计算机科学 2013-01-21 Keisuke Goto , Hideo Bannai

Converting a compressed format of a string into another compressed format without an explicit decompression is one of the central research topics in string processing. We discuss the problem of converting the run-length Burrows-Wheeler…

数据结构与算法 · 计算机科学 2019-02-15 Takaaki Nishimoto , Yasuo Tabei
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