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Related papers: Decompressing Lempel-Ziv Compressed Text

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The random access problem for compressed strings is to build a data structure that efficiently supports accessing the character in position $i$ of a string given in compressed form. Given a grammar of size $n$ compressing a string of size…

Data Structures and Algorithms · Computer Science 2015-01-27 Patrick Hagge Cording

A well-known fact in the field of lossless text compression is that high-order entropy is a weak model when the input contains long repetitions. Motivated by this, decades of research have generated myriads of so-called dictionary…

Data Structures and Algorithms · Computer Science 2020-12-17 Dominik Kempa , Nicola Prezza

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

It is shown that every tree of size $n$ over a fixed set of $\sigma$ different ranked symbols can be decomposed (in linear time as well as in logspace) into $O\big(\frac{n}{\log_\sigma n}\big) = O\big(\frac{n \log \sigma}{\log n}\big)$ many…

Data Structures and Algorithms · Computer Science 2015-09-22 Moses Ganardi , Danny Hucke , Artur Jez , Markus Lohrey , Eric Noeth

In grammar-based compression a string is represented by a context-free grammar, also called a straight-line program (SLP), that generates only that string. We refine a recent balancing result stating that one can transform an SLP of size…

Data Structures and Algorithms · Computer Science 2021-07-02 Moses Ganardi

Here we study the complexity of string problems as a function of the size of a program that generates input. We consider straight-line programs (SLP), since all algorithms on SLP-generated strings could be applied to processing…

Data Structures and Algorithms · Computer Science 2007-05-23 Yury Lifshits

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

Given $d$ strings over the alphabet $\{0,1,\ldots,\sigma{-}1\}$, the classical Aho--Corasick data structure allows us to find all $occ$ occurrences of the strings in any text $T$ in $O(|T| + occ)$ time using $O(m\log m)$ bits of space,…

Data Structures and Algorithms · Computer Science 2019-04-02 Dmitry Kosolobov , Nikita Sivukhin

Random access to highly compressed strings -- represented by straight-line programs or Lempel-Ziv parses, for example -- is a well-studied topic. Random access to such strings in strongly sublogarithmic time is impossible in the worst case,…

Data Structures and Algorithms · Computer Science 2026-02-05 Ferdinando Cicalese , Zsuzsanna Lipták , Travis Gagie , Gonzalo Navarro , Nicola Prezza , Cristian Urbina

We study the approximate string matching and regular expression matching problem for the case when the text to be searched is compressed with the Ziv-Lempel adaptive dictionary compression schemes. We present a time-space trade-off that…

Data Structures and Algorithms · Computer Science 2007-05-23 Philip Bille , Rolf Fagerberg , Inge Li Goertz

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

Relative Lempel-Ziv (RLZ) parsing is a dictionary compression method in which a string $S$ is compressed relative to a second string $R$ (called the reference) by parsing $S$ into a sequence of substrings that occur in $R$. RLZ is…

Data Structures and Algorithms · Computer Science 2022-08-25 Philip Bille , Inge Li Gørtz , Simon J. Puglisi , Simon R. Tarnow

We introduce height-bounded LZ encodings (LZHB), a new family of compressed representations that are variants of Lempel-Ziv parsings with a focus on bounding the worst-case access time to arbitrary positions in the text directly via the…

Data Structures and Algorithms · Computer Science 2024-04-26 Hideo Bannai , Mitsuru Funakoshi , Diptarama Hendrian , Myuji Matsuda , Simon J. Puglisi

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

In this paper we present a really simple linear-time algorithm constructing a context-free grammar of size O(g log (N/g)) for the input string, where N is the size of the input string and g the size of the optimal grammar generating this…

Data Structures and Algorithms · Computer Science 2014-03-19 Artur Jeż

The \emph{longest common extension} (\emph{LCE}) problem is to preprocess a given string $w$ of length $n$ so that the length of the longest common prefix between suffixes of $w$ that start at any two given positions is answered quickly. In…

Data Structures and Algorithms · Computer Science 2017-02-27 Yuka Tanimura , Takaaki Nishimoto , Hideo Bannai , Shunsuke Inenaga , Masayuki Takeda

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…

Data Structures and Algorithms · Computer Science 2019-02-15 Takaaki Nishimoto , Yasuo Tabei

We present a new algorithm for subsequence matching in grammar compressed strings. Given a grammar of size $n$ compressing a string of size $N$ and a pattern string of size $m$ over an alphabet of size $\sigma$, our algorithm uses…

Data Structures and Algorithms · Computer Science 2014-06-06 Philip Bille , Patrick Hagge Cording , Inge Li Gørtz

The complexity of computing the Lempel-Ziv factorization and the set of all runs (= maximal repetitions) is studied in the decision tree model of computation over ordered alphabet. It is known that both these problems can be solved by RAM…

Data Structures and Algorithms · Computer Science 2014-09-22 Dmitry Kosolobov

Real-world data often comes in compressed form. Analyzing compressed data directly (without decompressing it) can save space and time by orders of magnitude. In this work, we focus on fundamental sequence comparison problems and try to…

Data Structures and Algorithms · Computer Science 2021-12-14 Arun Ganesh , Tomasz Kociumaka , Andrea Lincoln , Barna Saha