29 citations · 45 across the 41 of their papers we have counts for
7 papers · 1 filter
Longest Property-Preserved Common Factor
Lorraine A. K Ayad, Giulia Bernardini, Roberto Grossi +4
In this paper we introduce a new family of string processing problems. We are given two or more strings and we are asked to compute a factor common to all strings that preserves a…
Efficient Computation of Sequence Mappability
Panagiotis Charalampopoulos, Costas S. Iliopoulos, Tomasz Kociumaka +3
In the -mappability problem, for a given sequence of length , the goal is to compute a table whose th entry is the number of indices such that the length…
Longest Unbordered Factor in Quasilinear Time
Tomasz Kociumaka, Ritu Kundu, Manal Mohamed +1
A border u of a word w is a proper factor of w occurring both as a prefix and as a suffix. The maximal unbordered factor of w is the longest factor of w which does not have a borde…
Alignment-free sequence comparison using absent words
Panagiotis Charalampopoulos, Maxime Crochemore, Gabriele Fici +2
Sequence comparison is a prerequisite to virtually all comparative genomic analyses. It is often realised by sequence alignment techniques, which are computationally expensive. Thi…
Longest Common Substring Made Fully Dynamic
Amihood Amir, Panagiotis Charalampopoulos, Solon P. Pissis +1
In the longest common substring (LCS) problem, we are given two strings and , each of length at most , and we are asked to find a longest string occurring as a fragment o…
Linear-Time Algorithm for Long LCF with Mismatches
Panagiotis Charalampopoulos, Maxime Crochemore, Costas S. Iliopoulos +5
In the Longest Common Factor with Mismatches (LCF) problem, we are given two strings and of total length , and we are asked to find a pair of maximal-length fact…
Longest Common Prefixes with -Errors and Applications
Lorraine A. K. Ayad, Panagiotis Charalampopoulos, Costas S. Iliopoulos +1
Although real-world text datasets, such as DNA sequences, are far from being uniformly random, average-case string searching algorithms perform significantly better than worst-case…