Journal ArticleDOI
Approximate graph edit distance computation by means of bipartite graph matching
Kaspar Riesen,Horst Bunke +1 more
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TLDR
A novel algorithm is introduced which allows us to approximately, or suboptimally, compute edit distance in a substantially faster way and is emprically verified that the accuracy of the suboptimal distance remains sufficiently accurate for various pattern recognition applications.About:
This article is published in Image and Vision Computing.The article was published on 2009-06-01. It has received 654 citations till now. The article focuses on the topics: Graph operations & Line graph.read more
Citations
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Journal ArticleDOI
Towards Accurate Subgraph Similarity Computation via Neural Graph Pruning
TL;DR: This work converts graph pruning to a problem of node relabeling and then relax it to a differentiable problem, and designs a novel neural network to approximate a type of subgraph distance: the subgraph edit distance (SED).
Proceedings ArticleDOI
Variational Deformation Method for the Computation of the Average Shape of Organs
Shun Inagaki,Atsushi Imiya +1 more
TL;DR: This work develops a variational method for the computation of average images of volumetric biological organs and obtains the average heart by leveraging the multiple warping to the temporal sequence of a beating heart.
Graph n-grams for Scientific Workflow Similarity Search.
TL;DR: This work explores a new structure-based approach to scientific workflow similarity assessment that measures similarity as the overlap in local structure patterns represented as n-grams and shows that this approach reaches state-of-the-art quality in scientific workflow comparison and outperforms some establishedscientific workflow similarity measures.
Journal ArticleDOI
Supervised learning for parameterized Koopmans-Beckmann's graph matching
TL;DR: In this article, a graph matching problem, namely the parameterized Koopmans-Beckmann's graph matching (KBGMw), is discussed, which is defined by a weighted linear combination of a series of Koopman and Beckmann graph matching.
Book ChapterDOI
Kernelising the ihara zeta function
TL;DR: This paper proposes to use the coefficients of reciprocal of Ihara Zeta Function for defining a kernel, and the proposed kernel is then applied to graph clustering.
References
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Journal ArticleDOI
The Protein Data Bank
Helen M. Berman,John D. Westbrook,Zukang Feng,Gary L. Gilliland,Talapady N. Bhat,Helge Weissig,Ilya N. Shindyalov,Philip E. Bourne +7 more
TL;DR: The goals of the PDB are described, the systems in place for data deposition and access, how to obtain further information and plans for the future development of the resource are described.
Journal ArticleDOI
The Hungarian method for the assignment problem
TL;DR: This paper has always been one of my favorite children, combining as it does elements of the duality of linear programming and combinatorial tools from graph theory, and it may be of some interest to tell the story of its origin this article.
Journal ArticleDOI
A Formal Basis for the Heuristic Determination of Minimum Cost Paths
TL;DR: How heuristic information from the problem domain can be incorporated into a formal mathematical theory of graph searching is described and an optimality property of a class of search strategies is demonstrated.
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