RASCAL: Calculation of Graph Similarity using Maximum Common Edge Subgraphs 论文
2002The Computer Journal引用 323
Graph Theory and AlgorithmsComplex Network Analysis TechniquesAdvanced Graph Neural Networks
摘要
A new graph similarity calculation procedure is introduced for comparing labeled graphs. Given a minimum similarity threshold, the procedure consists of an initial screening process to determine whether it is possible for the measure of similarity between the two graphs to exceed the minimum threshold, followed by a rigorous maximum common edge subgraph (MCES) detection algorithm to compute the exact degree and composition of similarity. The proposed MCES algorithm is based on a maximum clique formulation of the problem and is a significant improvement over other published algorithms. It presents new approaches to both lower and upper bounding as well as vertex selection. \n \n