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Journal ArticleDOI

Approximate graph edit distance computation by means of bipartite graph matching

Kaspar Riesen, +1 more
- 01 Jun 2009 - 
- Vol. 27, Iss: 7, pp 950-959
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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.

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Citations
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Journal ArticleDOI

Visual Analysis of Neural Architecture Spaces for Summarizing Design Principles

TL;DR: ArchExplorer as discussed by the authors is a visual analysis method for understanding a neural architecture space and summarizing design principles by exploiting structural distances between architectures, which can reduce the complexity of pairwise distance calculation to O(kn2N) by solving an allpairs shortest path problem.
Journal ArticleDOI

Computing Graph Edit Distance via Neural Graph Matching

TL;DR: In this paper , a graph neural network GEDGNN is proposed to predict the GED value and a matching matrix, and a post-processing algorithm based on the best matching is used to derive the possible node matchings from the matching matrix generated by GED-GNN.
Book ChapterDOI

Graph Embedding in Vector Spaces Using Matching-Graphs

TL;DR: In this article, a vectorial representation of a given graph is generated by generating hundreds of matching-graphs first, and then representing each graph g as a binary vector that shows the occurrence of each matching graph in g. In an experimental evaluation on three data sets, they show that this graph embedding is able to improve the classification accuracy of two reference systems with statistical significance.

Représentation par graphe de mots manuscrits dans les images pour la recherche par similarité

TL;DR: A novel handwritten word spotting approach based on graph representation that comprises both topological and morphological signatures of handwriting that outperforms the state-of-the-art structural methods.
References
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Journal ArticleDOI

The Protein Data Bank

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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