AbstractThe problem of computing the similarity of two run-length encoded strings has been studied for various scoring metrics. Many algorithms have been developed for the longest common subsequence metric and some algorithms for the Levenshtein distance metric and the weighted edit distance metric. In this paper we consider similarity based on the affine gap penalty metric which is a more general and rather complicated scoring metric than the weighted edit distance. To compute the similarity in this model efficiently, we convert the problem into a path problem on a directed acyclic graph and use some properties of maximum paths in this graph. We present an O(nm′+n′m) time algorithm for computing the similarity of two run-length encoded str...
We consider the following model for sampling pairs of strings: s? is a uniformly random bitstring of...
Edit distance is a fundamental measure of distance between strings, the extensive study of which has...
Data compression can be used to simultaneously reduce memory, communication and computation requirem...
AbstractThe problem of computing the similarity of two run-length encoded strings has been studied f...
International audienceGiven two strings of size n over a constant alphabet, the classical algorithm ...
Measuring the similarity between two strings, through such standard measures as Hamming distance, ed...
We show that the edit distance between two run-length encoded strings of compressed lengths m and n ...
Abstract Background The problem of approximate string matching is important in many different areas ...
Abstract. Given two strings ofsize n over a constant alphabet, the classical algorithm for computing...
[[abstract]]We propose a new algorithm for computing the edit distance of an uncompressed string aga...
AbstractThe well-known problem of the longest common subsequence (LCS), of two strings of lengths n ...
AbstractIn this paper, we consider a commonly used compression scheme called run-length encoding. We...
We prove the first nontrivial communication complexity lower bound for the problem of estimating the...
AbstractWe study approximate string-matching in connection with two string distance functions that a...
A common model for computing the similarity of two stringsXandYof lengthsm, andnrespectively with n,...
We consider the following model for sampling pairs of strings: s? is a uniformly random bitstring of...
Edit distance is a fundamental measure of distance between strings, the extensive study of which has...
Data compression can be used to simultaneously reduce memory, communication and computation requirem...
AbstractThe problem of computing the similarity of two run-length encoded strings has been studied f...
International audienceGiven two strings of size n over a constant alphabet, the classical algorithm ...
Measuring the similarity between two strings, through such standard measures as Hamming distance, ed...
We show that the edit distance between two run-length encoded strings of compressed lengths m and n ...
Abstract Background The problem of approximate string matching is important in many different areas ...
Abstract. Given two strings ofsize n over a constant alphabet, the classical algorithm for computing...
[[abstract]]We propose a new algorithm for computing the edit distance of an uncompressed string aga...
AbstractThe well-known problem of the longest common subsequence (LCS), of two strings of lengths n ...
AbstractIn this paper, we consider a commonly used compression scheme called run-length encoding. We...
We prove the first nontrivial communication complexity lower bound for the problem of estimating the...
AbstractWe study approximate string-matching in connection with two string distance functions that a...
A common model for computing the similarity of two stringsXandYof lengthsm, andnrespectively with n,...
We consider the following model for sampling pairs of strings: s? is a uniformly random bitstring of...
Edit distance is a fundamental measure of distance between strings, the extensive study of which has...
Data compression can be used to simultaneously reduce memory, communication and computation requirem...