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The Swap-Insert Correction distance from a string $S$ of length $n$ to another string $L$ of length $m\geq n$ on the alphabet $[1..d]$ is the minimum number of insertions, and swaps of pairs of adjacent symbols, converting $S$ into $L$.…

Data Structures and Algorithms · Computer Science 2015-06-30 Jérémy Barbay , Pablo Pérez-Lantero

We study the classical approximate string matching problem, that is, given strings $P$ and $Q$ and an error threshold $k$, find all ending positions of substrings of $Q$ whose edit distance to $P$ is at most $k$. Let $P$ and $Q$ have…

Data Structures and Algorithms · Computer Science 2011-03-21 Philip Bille

Edit distance between trees is a natural generalization of the classical edit distance between strings, in which the allowed elementary operations are contraction, uncontraction and relabeling of an edge. Demaine et al. [ACM Trans. on…

Data Structures and Algorithms · Computer Science 2018-04-27 Bartłomiej Dudek , Paweł Gawrychowski

We present novel randomized approximation schemes for the Edit Distance (ED) problem and the Longest Common Subsequence (LCS) problem that, for any constant $\epsilon>0$, compute a $(1+\epsilon)$-approximation for ED and a…

Data Structures and Algorithms · Computer Science 2026-04-01 Xiao Mao , Aviad Rubinstein

Let $T=t_0 ... t_{n-1}$ be a text and $P = p_0 ... p_{m-1}$ a pattern taken from some finite alphabet set $\Sigma$, and let $\dist$ be a metric on $\Sigma$. We consider the problem of calculating the sum of distances between the symbols of…

Data Structures and Algorithms · Computer Science 2008-02-12 Klim Efremenko , Ely Porat

We propose the neural string edit distance model for string-pair matching and string transduction based on learnable string edit distance. We modify the original expectation-maximization learned edit distance algorithm into a differentiable…

Computation and Language · Computer Science 2022-04-28 Jindřich Libovický , Alexander Fraser

We present an efficient algorithm for calculating $q$-gram frequencies on strings represented in compressed form, namely, as a straight line program (SLP). Given an SLP $\mathcal{T}$ of size $n$ that represents string $T$, the algorithm…

Data Structures and Algorithms · Computer Science 2013-05-27 Keisuke Goto , Hideo Bannai , Shunsuke Inenaga , Masayuki Takeda

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

Given a pattern string $P$ of length $n$ and a query string $T$ of length $m$, where the characters of $P$ and $T$ are drawn from an alphabet of size $\Delta$, the {\em exact string matching} problem consists of finding all occurrences of…

Data Structures and Algorithms · Computer Science 2015-10-01 Srikrishnan Divakaran

In the $k$-Edit Circular Pattern Matching ($k$-Edit CPM) problem, we are given a length-$n$ text $T$, a length-$m$ pattern $P$, and a positive integer threshold $k$, and we are to report all starting positions of the substrings of $T$ that…

Data Structures and Algorithms · Computer Science 2024-02-23 Panagiotis Charalampopoulos , Solon P. Pissis , Jakub Radoszewski , Wojciech Rytter , Tomasz Waleń , Wiktor Zuba

This paper deals with the two fundamental problems concerning the handling of large n-gram language models: indexing, that is compressing the n-gram strings and associated satellite data without compromising their retrieval speed; and…

Information Retrieval · Computer Science 2022-02-08 Giulio Ermanno Pibiri , Rossano Venturini

We study approximation algorithms for the following three string measures that are widely used in practice: edit distance (ED), longest common subsequence (LCS), and longest increasing sequence (LIS). All three problems can be solved…

Data Structures and Algorithms · Computer Science 2020-07-28 Kuan Cheng , Zhengzhong Jin , Xin Li , Yu Zheng

The algorithmic tasks of computing the Hamming distance between a given pattern of length $m$ and each location in a text of length $n$ is one of the most fundamental algorithmic tasks in string algorithms. Unfortunately, there is evidence…

Data Structures and Algorithms · Computer Science 2015-12-15 Tsvi Kopelowitz , Ely Porat

The edit distance $ed(X,Y)$ of two strings $X,Y\in \Sigma^*$ is the minimum number of character edits (insertions, deletions, and substitutions) needed to transform $X$ into $Y$. Its weighted counterpart $ed^w(X,Y)$ minimizes the total cost…

Data Structures and Algorithms · Computer Science 2025-07-04 Itai Boneh , Egor Gorbachev , Tomasz Kociumaka

Dot plots are a standard method for local comparison of biological sequences. In a dot plot, a substring to substring distance is computed for all pairs of fixed-size windows in the input strings. Commonly, the Hamming distance is used…

Data Structures and Algorithms · Computer Science 2009-09-11 Peter Krusche , Alexander Tiskin

The normalized edit distance is one of the distances derived from the edit distance. It is useful in some applications because it takes into account the lengths of the two strings compared. The normalized edit distance is not defined in…

Neural and Evolutionary Computing · Computer Science 2013-12-09 Muhammad Marwan Muhammad Fuad

String similarity, longest common subsequence and shortest edit scripts are the triplets of problem that related to each other. There are different algorithms exist to generate edit script by solving longest common subsequence problem. This…

Data Structures and Algorithms · Computer Science 2022-08-19 P. Prakash Maria Liju

Approximating the length of the longest increasing sequence (LIS) of an array is a well-studied problem. We study this problem in the data stream model, where the algorithm is allowed to make a single left-to-right pass through the array…

Data Structures and Algorithms · Computer Science 2013-04-16 Michael Saks , C. Seshadhri

In this paper we present a 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 string.…

Data Structures and Algorithms · Computer Science 2013-11-08 Artur Jeż

Given a string $T$ of length $N$, the goal of grammar compression is to construct a small context-free grammar generating only $T$. Among existing grammar compression methods, RePair (recursive paring) [Larsson and Moffat, 1999] is notable…

Data Structures and Algorithms · Computer Science 2018-11-06 Kensuke Sakai , Tatsuya Ohno , Keisuke Goto , Yoshimasa Takabatake , Tomohiro I , Hiroshi Sakamoto