We model the edit distance as a function in a labelling space. A labelling space is an Euclidean space where coordinates are the edit costs. Through this model, we define a class of cost. A class of cost is a region in the labelling space that all the edit costs have the same optimal labelling. Moreover, we characterise the distance value through the labelling space. This new point of view of the edit distance gives as the opportunity of defining some interesting properties that are useful for a better understanding of the edit distance. Finally, we show the usefulness of these properties through some applications
Reeb graphs are structural descriptors that capture shape properties of a topological space from the...
Graph editing distance is a measure of similarity or dissimilarity between two graphs. In this work,...
The edit distance (or Levenshtein distance) between two strings x, y is the minimum number of charac...
International audienceOne of the most popular distance measures between a pair of graphs is the Grap...
Although graph matching and graph edit distance computation have become areas of intensive research ...
Abstract. Generalized maps are widely used to model the topology of nD objects (such as 2D or 3D ima...
Graph edit distance measures the distance between two graphs as the number of elementary operations ...
The concept of graph edit distance constitutes one of the most flexible graph matching paradigms ava...
Abstract. In this paper we propose a quadratic programming approach to computing the edit distance o...
[[abstract]]One of the most important problem in computational biology is the tree editing problem w...
There are many types of sequences on which classification algorithms are applied. Sequences of symbo...
Graph edit distance is one of the most flexible mechanisms for error-tolerant graph matching. Its ke...
Abstract. The edit distance between two graphs on the same labeled vertex set is the size of the sym...
The edit distance function of a hereditary property is the asymptotically largest edit distance bet...
This paper presents a new method for computing the tree edit distance problem with uniform edit cost...
Reeb graphs are structural descriptors that capture shape properties of a topological space from the...
Graph editing distance is a measure of similarity or dissimilarity between two graphs. In this work,...
The edit distance (or Levenshtein distance) between two strings x, y is the minimum number of charac...
International audienceOne of the most popular distance measures between a pair of graphs is the Grap...
Although graph matching and graph edit distance computation have become areas of intensive research ...
Abstract. Generalized maps are widely used to model the topology of nD objects (such as 2D or 3D ima...
Graph edit distance measures the distance between two graphs as the number of elementary operations ...
The concept of graph edit distance constitutes one of the most flexible graph matching paradigms ava...
Abstract. In this paper we propose a quadratic programming approach to computing the edit distance o...
[[abstract]]One of the most important problem in computational biology is the tree editing problem w...
There are many types of sequences on which classification algorithms are applied. Sequences of symbo...
Graph edit distance is one of the most flexible mechanisms for error-tolerant graph matching. Its ke...
Abstract. The edit distance between two graphs on the same labeled vertex set is the size of the sym...
The edit distance function of a hereditary property is the asymptotically largest edit distance bet...
This paper presents a new method for computing the tree edit distance problem with uniform edit cost...
Reeb graphs are structural descriptors that capture shape properties of a topological space from the...
Graph editing distance is a measure of similarity or dissimilarity between two graphs. In this work,...
The edit distance (or Levenshtein distance) between two strings x, y is the minimum number of charac...