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Related papers: Packed Compact Tries: A Fast and Efficient Data St…

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Packing several characters into one computer word is a simple and natural way to compress the representation of a string and to speed up its processing. Exploiting this idea, we propose an index for a packed string, based on a {\em sparse…

Data Structures and Algorithms · Computer Science 2015-03-19 Roman Kolpakov , Gregory Kucherov , Tatiana Starikovskaya

We present a compressed representation of tries based on top tree compression [ICALP 2013] that works on a standard, comparison-based, pointer machine model of computation and supports efficient prefix search queries. Namely, we show how to…

Data Structures and Algorithms · Computer Science 2019-09-23 Philip Bille , Inge Li Gørtz , Paweł Gawrychowski , Gad M. Landau , Oren Weimann

In this paper, we introduce zip-tries, which are simple, dynamic, memory-efficient data structures for strings. Zip-tries support search and update operations for $k$-length strings in $\mathcal{O}(k+\log n)$ time in the standard RAM model…

Data Structures and Algorithms · Computer Science 2025-08-21 David Eppstein , Ofek Gila , Michael T. Goodrich , Ryuto Kitagawa

The suffix array and the suffix tree are the two most fundamental data structures for string processing. For a length-$n$ text, however, they use $\Theta(n \log n)$ bits of space, which is often too costly. To address this, Grossi and…

Data Structures and Algorithms · Computer Science 2023-04-20 Dominik Kempa , Tomasz Kociumaka

Given a dynamic set $K$ of $k$ strings of total length $n$ whose characters are drawn from an alphabet of size $\sigma$, a keyword dictionary is a data structure built on $K$ that provides locate, prefix search, and update operations on…

Data Structures and Algorithms · Computer Science 2020-10-08 Kazuya Tsuruta , Dominik Köppl , Shunsuke Kanda , Yuto Nakashima , Shunsuke Inenaga , Hideo Bannai , Masayuki Takeda

We show that the compressed suffix array and the compressed suffix tree for a string of length $n$ over an integer alphabet of size $\sigma\leq n$ can both be built in $O(n)$ (randomized) time using only $O(n\log\sigma)$ bits of working…

Data Structures and Algorithms · Computer Science 2016-05-24 Djamal Belazzougui

Given a string of length $n$ that is composed of $r$ runs of letters from the alphabet $\{0,1,\ldots,\sigma{-}1\}$ such that $2 \le \sigma \le r$, we describe a data structure that, provided $r \le n / \log^{\omega(1)} n$, stores the string…

Data Structures and Algorithms · Computer Science 2018-02-27 José Fuentes-Sepúlveda , Juha Kärkkäinen , Dmitry Kosolobov , Simon J. Puglisi

In the last decades, the necessity to process massive amounts of textual data fueled the development of compressed text indexes: data structures efficiently answering queries on a given text while occupying space proportional to the…

Data Structures and Algorithms · Computer Science 2024-09-24 Dominik Kempa , Tomasz Kociumaka

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

Suffix trees and suffix arrays are two of the most widely used data structures for text indexing. Each uses linear space and can be constructed in linear time for polynomially sized alphabets. However, when it comes to answering queries…

Data Structures and Algorithms · Computer Science 2013-11-08 Richard Cole , Tsvi Kopelowitz , Moshe Lewenstein

In this paper we describe compressed indexes that support pattern matching queries for strings with wildcards. For a constant size alphabet our data structure uses $O(n\log^{\varepsilon}n)$ bits for any $\varepsilon>0$ and reports all…

Data Structures and Algorithms · Computer Science 2014-01-06 Moshe Lewenstein , Yakov Nekrich , Jeffrey Scott Vitter

Suffix tree (and the closely related suffix array) are fundamental structures capturing all substrings of a given text essentially by storing all its suffixes in the lexicographical order. In some applications, we work with a subset of $b$…

Data Structures and Algorithms · Computer Science 2016-08-03 Paweł Gawrychowski , Tomasz Kociumaka

Tries are popular data structures for storing a set of strings, where common prefixes are represented by common root-to-node paths. Over fifty years of usage have produced many variants and implementations to overcome some of their…

Data Structures and Algorithms · Computer Science 2011-12-06 Roberto Grossi , Giuseppe Ottaviano

We propose a B tree representation storing $n$ keys, each of $k$ bits, in either (a) $nk + O(nk / \lg n)$ bits or (b) $nk + O(nk \lg \lg n/ \lg n)$ bits of space supporting all B tree operations in either (a) $O(\lg n )$ time or (b) $O(\lg…

Data Structures and Algorithms · Computer Science 2021-04-20 Tomohiro I , Dominik Köppl

Efficiently word storing and searching is an important task in computer science. An application space complexity, time complexity, and overall performance depend on this string data. Many word searching data structures and algorithms exist…

Data Structures and Algorithms · Computer Science 2019-11-06 Rahat Yeasin Emon , Sharmistha Chanda Tista

The notions of synchronizing and partitioning sets are recently introduced variants of locally consistent parsings with great potential in problem-solving. In this paper we propose a deterministic algorithm that constructs for a given…

Data Structures and Algorithms · Computer Science 2024-04-23 Dmitry Kosolobov , Nikita Sivukhin

We show that the compressed suffix array and the compressed suffix tree of a string $T$ can be built in $O(n)$ deterministic time using $O(n\log\sigma)$ bits of space, where $n$ is the string length and $\sigma$ is the alphabet size.…

Data Structures and Algorithms · Computer Science 2016-11-15 J. Ian Munro , Gonzalo Navarro , Yakov Nekrich

An indexed sequence of strings is a data structure for storing a string sequence that supports random access, searching, range counting and analytics operations, both for exact matches and prefix search. String sequences lie at the core of…

Data Structures and Algorithms · Computer Science 2012-04-17 Roberto Grossi , Giuseppe Ottaviano

Given strings $P$ and $Q$ the (exact) string matching problem is to find all positions of substrings in $Q$ matching $P$. The classical Knuth-Morris-Pratt algorithm [SIAM J. Comput., 1977] solves the string matching problem in linear time…

Data Structures and Algorithms · Computer Science 2010-09-08 Philip Bille

We propose new succinct representations of ordinal trees, which have been studied extensively. It is known that any $n$-node static tree can be represented in $2n + o(n)$ bits and a number of operations on the tree can be supported in…

Data Structures and Algorithms · Computer Science 2010-09-27 Gonzalo Navarro , Kunihiko Sadakane
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