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The edit distance between two strings is defined as the smallest number of insertions, deletions, and substitutions that need to be made to transform one of the strings to another one. Approximating edit distance in subquadratic time is…

Data Structures and Algorithms · Computer Science 2018-04-27 Mahdi Boroujeni , Soheil Ehsani , Mohammad Ghodsi , MohammadTaghi HajiAghayi , Saeed Seddighin

We study the problem of approximating the edit distance of two strings in sublinear time, in a setting where one or both string(s) are preprocessed, as initiated by Goldenberg, Rubinstein, Saha (STOC '20). Specifically, in the $(k, K)$-gap…

Data Structures and Algorithms · Computer Science 2022-10-13 Karl Bringmann , Alejandro Cassis , Nick Fischer , Vasileios Nakos

Given a context free language $\mathcal{L(G)}$ over alphabet $\Sigma$ and a string $s \in \Sigma^*$, {\em the language edit distance} problem seeks the minimum number of edits (insertions, deletions and substitutions) required to convert…

Data Structures and Algorithms · Computer Science 2024-10-25 Tomasz Kociumaka , Barna Saha

Tree edit distance is a well-studied measure of dissimilarity between rooted trees with node labels. It can be computed in $O(n^3)$ time [Demaine, Mozes, Rossman, and Weimann, ICALP 2007], and fine-grained hardness results suggest that the…

Data Structures and Algorithms · Computer Science 2021-06-11 Shyan Akmal , Ce Jin

We present an algorithm for approximating the edit distance between two strings of length $n$ in time $n^{1+\varepsilon}$ up to a constant factor, for any $\varepsilon>0$. Our result completes a research direction set forth in the recent…

Data Structures and Algorithms · Computer Science 2022-07-18 Alexandr Andoni , Negev Shekel Nosatzki

We consider the following model for sampling pairs of strings: $s_1$ is a uniformly random bitstring of length $n$, and $s_2$ is the bitstring arrived at by applying substitutions, insertions, and deletions to each bit of $s_1$ with some…

Data Structures and Algorithms · Computer Science 2020-07-08 Arun Ganesh , Aaron Sy

The {\em edit distance} between two ordered trees with vertex labels is the minimum cost of transforming one tree into the other by a sequence of elementary operations consisting of deleting and relabeling existing nodes, as well as…

Data Structures and Algorithms · Computer Science 2010-12-01 Erik D. Demaine , Shay Mozes , Benjamin Rossman , Oren Weimann

We present the first dynamic algorithms for Dyck and tree edit distances with subpolynomial update times. Dyck edit distance measures how far a parenthesis string is from a well-parenthesized expression, while tree edit distance quantifies…

Data Structures and Algorithms · Computer Science 2025-10-21 Debarati Das , Jacob Gilbert , MohammadTaghi Hajiaghayi , Tomasz Kociumaka , Barna Saha

We give an $\tilde O(n^2)$ time algorithm for computing the exact Dynamic Time Warping distance between two strings whose run-length encoding is of size at most $n$. This matches (up to log factors) the known (conditional) lower bound, and…

Data Structures and Algorithms · Computer Science 2023-02-14 Itai Boneh , Shay Golan , Shay Mozes , Oren Weimann

We show how to compute the edit distance between two strings of length n up to a factor of 2^{\~O(sqrt(log n))} in n^(1+o(1)) time. This is the first sub-polynomial approximation algorithm for this problem that runs in near-linear time,…

Data Structures and Algorithms · Computer Science 2011-09-27 Alexandr Andoni , Krzysztof Onak

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

We consider the approximate pattern matching problem under the edit distance. Given a text $T$ of length $n$, a pattern $P$ of length $m$, and a threshold $k$, the task is to find the starting positions of all substrings of $T$ that can be…

Data Structures and Algorithms · Computer Science 2022-04-08 Panagiotis Charalampopoulos , Tomasz Kociumaka , Philip Wellnitz

We study the problem of approximating edit distance in sublinear time. This is formalized as the $(k,k^c)$-Gap Edit Distance problem, where the input is a pair of strings $X,Y$ and parameters $k,c>1$, and the goal is to return YES if…

Data Structures and Algorithms · Computer Science 2022-10-04 Elazar Goldenberg , Tomasz Kociumaka , Robert Krauthgamer , Barna Saha

We show that the edit distance between two run-length encoded strings of compressed lengths $m$ and $n$ respectively, can be computed in $\mathcal{O}(mn\log(mn))$ time. This improves the previous record by a factor of…

Data Structures and Algorithms · Computer Science 2019-05-06 Raphaël Clifford , Paweł Gawrychowski , Tomasz Kociumaka , Daniel P. Martin , Przemysław Uznański

Classic similarity measures of strings are longest common subsequence and Levenshtein distance (i.e., the classic edit distance). A classic similarity measure of curves is dynamic time warping. These measures can be computed by simple…

Computational Complexity · Computer Science 2015-04-06 Karl Bringmann , Marvin Künnemann

The edit distance between two words $w_1, w_2$ is the minimal number of word operations (letter insertions, deletions, and substitutions) necessary to transform $w_1$ to $w_2$. The edit distance generalizes to languages $\mathcal{L}_1,…

Formal Languages and Automata Theory · Computer Science 2019-03-14 Krishnendu Chatterjee , Thomas A. Henzinger , Rasmus Ibsen-Jensen , Jan Otop

The edit distance between strings classically assigns unit cost to every character insertion, deletion, and substitution, whereas the Hamming distance only allows substitutions. In many real-life scenarios, insertions and deletions…

Data Structures and Algorithms · Computer Science 2026-02-23 Elazar Goldenberg , Tomasz Kociumaka , Robert Krauthgamer , Barna Saha

Many problems that can be solved in quadratic time have bit-parallel speed-ups with factor $w$, where $w$ is the computer word size. For example, edit distance of two strings of length $n$ can be solved in $O(n^2/w)$ time. In a reasonable…

Quantum Physics · Physics 2023-02-07 Massimo Equi , Arianne Meijer-van de Griend , Veli Mäkinen

We present a near-linear time algorithm that approximates the edit distance between two strings within a polylogarithmic factor; specifically, for strings of length n and every fixed epsilon>0, it can compute a (log n)^O(1/epsilon)…

Data Structures and Algorithms · Computer Science 2010-05-24 Alexandr Andoni , Robert Krauthgamer , Krzysztof Onak

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