On a relation between graph edit distance and maximum common subgraph
Pattern Recognition Letters
A New Algorithm for Error-Tolerant Subgraph Isomorphism Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition Letters - Special issue on pattern recognition in practice VI
On Median Graphs: Properties, Algorithms, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Median graph: A new exact algorithm using a distance based on the maximum common subgraph
Pattern Recognition Letters
Median graphs: A genetic approach based on new theoretical properties
Pattern Recognition
Learning graph prototypes for shape recognition
Computer Vision and Image Understanding
Entropy versus heterogeneity for graphs
GbRPR'11 Proceedings of the 8th international conference on Graph-based representations in pattern recognition
Characterizing graphs using approximate von Neumann entropy
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Graph characterizations from von Neumann entropy
Pattern Recognition Letters
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Given a set of elements, the median can be a useful concept to get a representative that captures the global information of the set. In the domain of structural pattern recognition, the median of a set of graphs has also been defined and some properties have been derived. In addition, the maximum common subgraph of a set of graphs is a well known concept that has various applications in pattern recognition. The computation of both the median and the maximum common subgraph are highly complex tasks. Therefore, for practical reasons, some strategies are used to reduce the search space and obtain approximate solutions for the median graph. The bounds on the sum of distances of the median graph to all the graphs in the set turns out to be useful in the definition of such strategies. In this paper, we reduce the upper bound of the sum of distances of the median graph and we relate it to the maximum common subgraph.