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We show how to compress string dictionaries using the Lempel-Ziv (LZ78) data compression algorithm. Our approach is validated experimentally on dictionaries of up to 1.5 GB of uncompressed text. We achieve compression ratios often…

Data Structures and Algorithms · Computer Science 2013-05-06 Julian Arz , Johannes Fischer

We present a simple adaptation of the Lempel Ziv 78' (LZ78) compression scheme ({\em IEEE Transactions on Information Theory, 1978}) that supports efficient random access to the input string. Namely, given query access to the compressed…

Data Structures and Algorithms · Computer Science 2013-01-14 Akashnil Dutta , Reut Levi , Dana Ron , Ronitt Rubinfeld

Computation on compressed strings is one of the key approaches to processing massive data sets. We consider local subsequence recognition problems on strings compressed by straight-line programs (SLP), which is closely related to…

Data Structures and Algorithms · Computer Science 2011-11-10 Alexander Tiskin

The Lempel--Ziv 78 (LZ78) factorization is a well-studied technique for data compression. It and its derivatives are used in compression formats such as "compress" or "gif". Although most research focuses on the factorization of plain data,…

Data Structures and Algorithms · Computer Science 2025-12-22 Hiroki Shibata , Dominik Köppl

We tackle the problems of computing the rightmost variant of the Lempel-Ziv factorizations in the online/sliding model. Previous best bounds for this problem are O(n log n) time with O(n) space, due to Amir et al. [IPL 2002] for the online…

Data Structures and Algorithms · Computer Science 2024-08-07 Wataru Sumiyoshi , Takuya Mieno , Shunsuke Inenaga

We present an algorithm that computes the Lempel-Ziv decomposition in $O(n(\log\sigma + \log\log n))$ time and $n\log\sigma + \epsilon n$ bits of space, where $\epsilon$ is a constant rational parameter, $n$ is the length of the input…

Data Structures and Algorithms · Computer Science 2015-06-09 Dmitry Kosolobov

We propose algorithms computing the semi-greedy Lempel-Ziv 78 (LZ78), the Lempel-Ziv Double (LZD), and the Lempel-Ziv-Miller-Wegman (LZMW) factorizations in linear time for integer alphabets. For LZD and LZMW, we additionally propose data…

Data Structures and Algorithms · Computer Science 2024-09-24 Dominik Köppl

Sublinear time quantum algorithms have been established for many fundamental problems on strings. This work demonstrates that new, faster quantum algorithms can be designed when the string is highly compressible. We focus on two popular and…

Data Structures and Algorithms · Computer Science 2023-02-15 Daniel Gibney , Sharma V. Thankachan

In this paper, we propose a new \emph{dynamic compressed index} of $O(w)$ space for a dynamic text $T$, where $w = O(\min(z \log N \log^*M, N))$ is the size of the signature encoding of $T$, $z$ is the size of the Lempel-Ziv77 (LZ77)…

Data Structures and Algorithms · Computer Science 2016-07-20 Takaaki Nishimoto , Tomohiro I , Shunsuke Inenaga , Hideo Bannai , Masayuki Takeda

We present an algorithm which computes the Lempel-Ziv factorization of a word $W$ of length $n$ on an alphabet $\Sigma$ of size $\sigma$ online in the following sense: it reads $W$ starting from the left, and, after reading each $r =…

Data Structures and Algorithms · Computer Science 2012-12-03 Tatiana Starikovskaya

We raise the question of approximating the compressibility of a string with respect to a fixed compression scheme, in sublinear time. We study this question in detail for two popular lossless compression schemes: run-length encoding (RLE)…

Data Structures and Algorithms · Computer Science 2007-06-11 Sofya Raskhodnikova , Dana Ron , Ronitt Rubinfeld , Adam Smith

The well-known dictionary-based algorithms of the Lempel-Ziv (LZ) 77 family are the basis of several universal lossless compression techniques. These algorithms are asymmetric regarding encoding/decoding time and memory requirements, with…

Data Structures and Algorithms · Computer Science 2009-12-31 Artur Ferreira , Arlindo Oliveira , Mario Figueiredo

Classically, the edit distance of two length-$n$ strings can be computed in $O(n^2)$ time, whereas an $O(n^{2-\epsilon})$-time procedure would falsify the Orthogonal Vectors Hypothesis. If the edit distance does not exceed $k$, the running…

Data Structures and Algorithms · Computer Science 2023-11-06 Daniel Gibney , Ce Jin , Tomasz Kociumaka , Sharma V. Thankachan

An LZ-like factorization of a string divides it into factors, each being either a single character or a copy of a preceding substring. While grammar-based compression schemes support efficient random access with space linear in the…

Data Structures and Algorithms · Computer Science 2026-01-22 Hiroki Shibata , Yuto Nakashima , Yutaro Yamaguchi , Shunsuke Inenaga

We investigate two closely related LZ78-based compression schemes: LZMW (an old scheme by Miller and Wegman) and LZD (a recent variant by Goto et al.). Both LZD and LZMW naturally produce a grammar for a string of length $n$; we show that…

Data Structures and Algorithms · Computer Science 2017-07-26 Golnaz Badkobeh , Travis Gagie , Shunsuke Inenaga , Tomasz Kociumaka , Dmitry Kosolobov , Simon J. Puglisi

We present an algorithm for computing the Lyndon factorization of a string that is given in grammar compressed form, namely, a Straight Line Program (SLP). The algorithm runs in $O(n^4 + mn^3h)$ time and $O(n^2)$ space, where $m$ is the…

Data Structures and Algorithms · Computer Science 2013-04-29 Tomohiro I , Yuto Nakashima , Shunsuke Inenaga , Hideo Bannai , Masayuki Takeda

In this paper, we present the following results: (1) We propose a new \emph{dynamic compressed index} of $O(w)$ space, that supports searching for a pattern $P$ in the current text in $O(|P| f(M,w) + \log w \log |P| \log^* M (\log N + \log…

Data Structures and Algorithms · Computer Science 2016-04-07 Takaaki Nishimoto , I Tomohiro , Shunsuke Inenaga , Hideo Bannai , Masayuki Takeda

Given an LZW/LZ78 compressed text, we want to find an approximate occurrence of a given pattern of length m. The goal is to achieve time complexity depending on the size n of the compressed representation of the text instead of its length.…

Data Structures and Algorithms · Computer Science 2013-09-23 Pawel Gawrychowski , Damian Straszak

LZ77-based compression schemes compress the input text by replacing factors in the text with an encoded reference to a previous occurrence formed by the couple (length, offset). For a given factor, the smallest is the offset, the smallest…

Data Structures and Algorithms · Computer Science 2012-11-22 Maxime Crochemore , Alessio Langiu , Filippo Mignosi

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…

Data Structures and Algorithms · Computer Science 2015-10-22 Nicola Prezza , Alberto Policriti