The graph isomorphism problem: its structural complexity
The graph isomorphism problem: its structural complexity
Journal of Algorithms
Shape matching using edit-distance: an implementation
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Recognition of Shapes by Editing Their Shock Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Vectors from Algebraic Graph Theory
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey on tree edit distance and related problems
Theoretical Computer Science
Edit distance-based kernel functions for structural pattern classification
Pattern Recognition
Graph embedding using tree edit-union
Pattern Recognition
A study of graph spectra for comparing graphs and trees
Pattern Recognition
Graph clustering using the weighted minimum common supergraph
GbRPR'03 Proceedings of the 4th IAPR international conference on Graph based representations in pattern recognition
Graph embedding in vector spaces by means of prototype selection
GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition
Graph matching – challenges and potential solutions
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
Self-organizing maps for learning the edit costs in graph matching
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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In pattern recognition, graphs become alluring more and more as structural pattern representations due to their richer representability than feature vectors. However, there are many challenging problems using graphs for pattern recognition. One is that it is difficult to investigate the relationships of graphs effectively, even of trees. In this paper, we focus on the structure relationship analysis of trees, such as tree and subtree isomorphism, maximum common subtree, minimum common supertree, etc., which is almost suffered from all kinds of tree recognition problems. For investigating the relationships of structures of trees, we propose a structure network to represent the evolutional relationships of structures of trees. Moreover, for a lot of tree isomorphism problems appearing in the application of structure network, we propose a method that encodes the structure of tree as a numerical sequence, and illustrate its efficiency by comparing it with traditional matching method for tree isomorphism problem.