The ARG Database is a huge collection of labeled and unlabeled graphs realized by the MIVIA Group.
The aim of this collection is to provide the graph research community with a standard test ground for the benchmarking of graph matching algorithms.The database is organized in two section: labeled and unlabeled graphs.
Both labeled and unlabeled graphs have been randomly generated according to six different generation models, each involving different possible parameter settings. As a result, 168 diverse kinds of graphs are contained in the database. Each type of unlabeled graph is represented by thousands of pairs of graphs for which an isomorphism or a graph-subgraph isomorphism relation holds, for a total of 143,600 graphs. Furthermore, each type of labeled graph is represented by thousands of pairs of graphs holding a not trivial common subgraph, for a total of 166,000 graphs.
The dataset was published in
De Santo, M., Foggia, P., Sansone, C., & Vento, M. (2003). A large database of graphs and its use for benchmarking graph isomorphism algorithms. Pattern Recognition Letters, 24(8), 1067-1079. https://doi.org/10.1016/S0167-8655(02)00253-2
The original data was downloaded from https://zenodo.org/records/11204020
