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ICPR
2004
IEEE
14 years 5 months ago
A Probabilistic Approach to Learning Costs for Graph Edit Distance
Graph edit distance provides an error-tolerant way to measure distances between attributed graphs. The effectiveness of edit distance based graph classification algorithms relies ...
Horst Bunke, Michel Neuhaus
ISCI
2007
170views more  ISCI 2007»
13 years 4 months ago
Automatic learning of cost functions for graph edit distance
Graph matching and graph edit distance have become important tools in structural pattern recognition. The graph edit distance concept allows us to measure the structural similarit...
Michel Neuhaus, Horst Bunke
GBRPR
2007
Springer
13 years 10 months ago
A Quadratic Programming Approach to the Graph Edit Distance Problem
In this paper we propose a quadratic programming approach to computing the edit distance of graphs. Whereas the standard edit distance is defined with respect to a minimum-cost ed...
Michel Neuhaus, Horst Bunke
ICDM
2007
IEEE
187views Data Mining» more  ICDM 2007»
13 years 11 months ago
Statistical Learning Algorithm for Tree Similarity
Tree edit distance is one of the most frequently used distance measures for comparing trees. When using the tree edit distance, we need to determine the cost of each operation, bu...
Atsuhiro Takasu, Daiji Fukagawa, Tatsuya Akutsu
ECML
2007
Springer
13 years 10 months ago
Learning Metrics Between Tree Structured Data: Application to Image Recognition
The problem of learning metrics between structured data (strings, trees or graphs) has been the subject of various recent papers. With regard to the specific case of trees, some a...
Laurent Boyer 0002, Amaury Habrard, Marc Sebban