We consider in this paper the similarity search problem that retrieves relevant graphs from a
graph database under the well-known graph edit distance (GED) constraint. Formally, given …

Graph similarity is a basic and essential operation in many applications. In this paper, we
are interested in computing graph similarity based on edit distance. Existing graph edit …

Graph edit distance (GED) computation is a fundamental NP-hard problem in graph theory.
Given a graph pair (G 1, G 2), GED is defined as the minimum number of primitive …

We study the problem of graph similarity search with a graph edit distance (GED) constraint.
Existing solutions adopt a filteringand-verification framework, with a focus on the filtering …

Graph similarity search is to retrieve all graphs from a graph database whose graph edit
distance (GED) to a query graph is within a given threshold. As GED computation is NP …

Graph similarity search is a crucial problem in many applications, such as cheminformatics,
data mining, and pattern recognition. Top-k graph similarity search aims to find the most …

Graphs have been widely used for complex data representation in many real applications,
such as social network, bioinformatics, and computer vision. Therefore, graph similarity join …

Graph similarity search under the graph edit distance constraint has received considerable
attention in many applications, such as bioinformatics, data mining, pattern recognition and …

Many real-world applications, such as bioinformatics, data mining, pattern recognition, and
social network analysis, benefit from efficient solutions for the graph similarity search …

Given a graph pair $(G^ 1, G^ 2) $, graph edit distance (GED) is defined as the minimum
number of edit operations converting $ G^ 1$ to $ G^ 2$. GED is a fundamental operation …