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 edit distance (GED) is a measure for quantifying the similarity between two graphs.
Because of its flexibility and versatility, GED is widely used in many real applications …

This survey article considers index structures for fast similarity search for objects
represented by trees and graphs. Edit distance is used as a measure of similarity. The …

Semantic Similarity (SS) has become a long-standing research domain in artificial
intelligence and cognitive science for measuring the strength of the semantic relationship …

Similarity calculation of large-scale graphs is essential in big data classification, sorting, and
other work. However, when there are diverse attributes and the vertices are not ordered, the …

Graphs are widely used to model many real-world data in many application domains such
as chemical compounds, protein structures, gene structures, metabolic pathways …

In this paper, we study the problem of graph similarity search with graph edit distance (GED)
constraints. Due to the NP-hardness of GED computation, existing solutions to this problem …

Algorithms that can accurately determine the similarity of directed graphs often need a heavy
overhead. In order to save time and achieve a better balance between performance cost and …