Graph-based representation for similarity retrieval of symbolic images
Data & Knowledge Engineering
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
Efficient mining of top-k breaker emerging subgraph patterns from graph datasets
AusDM '09 Proceedings of the Eighth Australasian Data Mining Conference - Volume 101
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Graph representations are widely used for dealing with structural information. There are applications, for example, in pattern recognition, machine learning and information retrieval, where one needs to measure the similarity of objects. When graphs are used for the representation of structured objects, then measuring the similarity of objects becomes equivalent to determining the similarity of graphs. The measurement of similarity is normally performed by determining the maximum common subgraph of the graphs in question. This paper presents a new algorithm for determining the maximum common subgraph of a pair of graphs which offers better performance than existing algorithms.