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In today's data-centric world, fast and effective compression of data is paramount. To measure success towards the second goal, Kempa and Prezza [STOC2018] introduce the string attractor, a combinatorial object unifying dictionary-based…

Data Structures and Algorithms · Computer Science 2024-07-23 Philip Whittington

Let $S$ be a string of length $n$. In this paper we introduce the notion of \emph{string attractor}: a subset of the string's positions $[1,n]$ such that every distinct substring of $S$ has an occurrence crossing one of the attractor's…

Data Structures and Algorithms · Computer Science 2017-09-20 Nicola Prezza

String attractors [STOC 2018] are combinatorial objects recently introduced to unify all known dictionary compression techniques in a single theory. A set $\Gamma\subseteq [1..n]$ is a $k$-attractor for a string $S\in[1..\sigma]^n$ if and…

Data Structures and Algorithms · Computer Science 2020-12-09 Dominik Kempa , Alberto Policriti , Nicola Prezza , Eva Rotenberg

A $k$-attractor is a combinatorial object unifying dictionary-based compression. It allows to compare the repetitiveness measures of different dictionary compressors such as Lempel-Ziv 77, the Burrows-Wheeler transform, straight line…

Computational Complexity · Computer Science 2024-02-08 Janosch Fuchs , Philip Whittington

The rise of repetitive datasets has lately generated a lot of interest in compressed self-indexes based on dictionary compression, a rich and heterogeneous family that exploits text repetitions in different ways. For each such compression…

Data Structures and Algorithms · Computer Science 2020-12-17 Gonzalo Navarro , Nicola Prezza

The notion of string attractor has been introduced in [Kempa and Prezza, 2018] in the context of Data Compression and it represents a set of positions of a finite word in which all of its factors can be "attracted". The smallest size…

Formal Languages and Automata Theory · Computer Science 2022-06-02 Antonio Restivo , Giuseppe Romana , Marinella Sciortino

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

The notion of \emph{string attractor} has recently been introduced in [Prezza, 2017] and studied in [Kempa and Prezza, 2018] to provide a unifying framework for known dictionary-based compressors. A string attractor for a word…

Data Structures and Algorithms · Computer Science 2019-07-11 Sabrina Mantaci , Antonio Restivo , Giuseppe Romana , Giovanna Rosone , Marinella Sciortino

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

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

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

One of the most famous and investigated lossless data-compression scheme is the one introduced by Lempel and Ziv about 40 years ago. This compression scheme is known as "dictionary-based compression" and consists of squeezing an input…

Data Structures and Algorithms · Computer Science 2008-02-07 Paolo Ferragina , Igor Nitto , Rossano Venturini

The article focuses on word (or string) attractors, which are sets of positions related to the text compression efficiency of the underlying word. The article presents two combinatorial algorithms based on Suffix automata or Directed…

Data Structures and Algorithms · Computer Science 2025-09-11 Marie-Pierre Béal , Maxime Crochemore , Giuseppe Romana

This thesis concerns sequential-access data compression, i.e., by algorithms that read the input one or more times from beginning to end. In one chapter we consider adaptive prefix coding, for which we must read the input character by…

Information Theory · Computer Science 2009-02-03 Travis Gagie

Shannon's entropy is a definitive lower bound for statistical compression. Unfortunately, no such clear measure exists for the compressibility of repetitive strings. Thus, ad hoc measures are employed to estimate the repetitiveness of…

Data Structures and Algorithms · Computer Science 2023-11-16 Giulia Bernardini , Gabriele Fici , Paweł Gawrychowski , Solon P. Pissis

Grammar based compression, where one replaces a long string by a small context-free grammar that generates the string, is a simple and powerful paradigm that captures many popular compression schemes. In this paper, we present a novel…

Data Structures and Algorithms · Computer Science 2013-10-30 Philip Bille , Gad M. Landau , Rajeev Raman , Kunihiko Sadakane , Srinivasa Rao Satti , Oren Weimann

We describe the first self-indexes able to count and locate pattern occurrences in optimal time within a space bounded by the size of the most popular dictionary compressors. To achieve this result we combine several recent findings,…

Data Structures and Algorithms · Computer Science 2019-09-06 Anders Roy Christiansen , Mikko Berggren Ettienne , Tomasz Kociumaka , Gonzalo Navarro , Nicola Prezza

Most of the fastest-growing string collections today are repetitive, that is, most of the constituent documents are similar to many others. As these collections keep growing, a key approach to handling them is to exploit their…

Information Retrieval · Computer Science 2017-05-22 Travis Gagie , Aleksi Hartikainen , Kalle Karhu , Juha Kärkkäinen , Gonzalo Navarro , Simon J. Puglisi , Jouni Sirén

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

Compression techniques that support fast random access are a core component of any information system. Current state-of-the-art methods group documents into fixed-sized blocks and compress each block with a general-purpose adaptive…

Data Structures and Algorithms · Computer Science 2015-03-19 Christopher Hoobin , Simon J. Puglisi , Justin Zobel
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