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
Generic Object Recognition Using Graph Embedding into A Vector Space
TL;DR: In the proposed method, the graph is constructed by connecting SIFT keypoints with lines, and then structural representation with location information is achieved and the recognition rate is improved.
Proceedings Article
Evaluating Sketch-Based Retrieval Speed-Up for Behaviour Design in Soccerbots.
TL;DR: The design and results from an experiment designed to measure to what extent having a library of reusable behaviours accessed through sketch-based retrieval can speed-up the behaviour design process in the Soccerbots game are described.
Proceedings ArticleDOI
A Weighted Distance Learning Method for Graph Classification
TL;DR: A weighted distance-learning method is used, in this paper, to optimize the accuracy of Nearest-Neighbour classifier for a graph-based data set, and the uniformly good behaviour of the proposed method is presented having results competitive with the related methods.
Posted Content
An interdisciplinary survey of network similarity methods.
Emily J. Evans,Marissa Graham +1 more
TL;DR: An integrative introduction to the key objectives and methods of graph and network comparison in each field are presented, with the intent of remaining accessible to relative novices in order to mitigate the barrier to interdisciplinary idea crossover.
Posted Content
Metric Indexing for Graph Similarity Search
TL;DR: In this article, a filter-verification framework for similarity search is proposed, which supports non-uniform edit costs for graphs with arbitrary attributes, and employs an expensive lower bound obtained by solving an optimal assignment problem.
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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