title = "Graph edit distance contest: Results and future challenges", journal = "Pattern Recognition Letters", volume = "100", number = "Supplement C", pages = "96 - 103", year = "2017", issn = "0167-8655", doi = "https://doi.org/10.1016/j.patrec.2017.10.007", url = "HAL:=https://hal.archives-ouvertes.fr/hal-01624592, ScienceDirect:=http://www.sciencedirect.com/science/article/pii/S0167865517303690", author = "Zeina Abu-Aisheh and Benoit Gaüzère and Sébastien Bougleux and Jean-Yves Ramel and Luc Brun and Romain Raveaux and Pierre H'eroux and Sébastien Adam", keywords = "Graph edit distance, Pattern Recognition, Binary linear programming, Quadratic assignment, Branch-and-bound", theme={pattern,ged}, abstract = "Abstract Graph Distance Contest (GDC) was organized in the context of ICPR 2016. Its main challenge was to inspect and report performances and effectiveness of exact and approximate graph edit distance methods by comparison with a ground truth. This paper presents the context of this competition, the metrics and datasets used for evaluation, and the results obtained by the eight submitted methods. Results are analyzed and discussed in terms of computation time and accuracy. We also highlight the future challenges in graph edit distance regarding both future methods and evaluation metrics. The contest was supported by the Technical Committee on Graph-Based Representations in Pattern Recognition (TC-15) of the International Association of Pattern Recognition (IAPR)."