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Learning Heuristics to Reduce the Overestimation of Bipartite Graph Edit Distance Approximation
In data mining systems, which operate on complex data with structural relationships, graphs are often used to represent the basic objects under study. Yet, the high representational power of graphs is also accompanied by ...
Suboptimal Graph Edit Distance Based on Sorted Local Assignments
Graph based pattern representation offers a number of useful properties. In particular, graphs can adapt their size and complexity to the actual pattern, and moreover, graphs are able to describe structural relations that ...
Kernel k-means Clustering applied to Vector Space Embeddings of Graphs.
(LNAI 5064, 2008-01-01)
Improving Hausdorff Edit Distance Using Structural Node Context
In order to cope with the exponential time complexity of graph edit distance, several polynomial-time approximation algorithms have been proposed in recent years. The Hausdorff edit distance is a quadratic-time matching ...
A First Step Towards Exact Graph Edit Distance Using Bipartite Graph Matching
In recent years, a powerful approximation framework for graph edit distance computation has been introduced. This particular approximation is based on an optimal assignment of local graph structures which can be established ...
Computing Upper and Lower Bounds of Graph Edit Distance in Cubic Time
Exact computation of graph edit distance (GED) can be solved in exponential time complexity only. A previously introduced approximation framework reduces the computation of GED to an instance of a linear sum assignment ...