Journal ArticleDOI
Approximate graph edit distance computation by means of bipartite graph matching
Kaspar Riesen,Horst Bunke +1 more
Reads0
Chats0
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
More filters
People Re-identification by Graph Kernel Methods
TL;DR: In this paper, a graph description of each person is used to apply principal component analysis (PCA) to the graph domain, and the graph kernel is applied to two video sequences from the PETS2009 database.
Posted Content
A Quotient Space Formulation for Statistical Analysis of Graphical Data.
TL;DR: A quotient structure is utilizes to develop efficient algorithms for computing these quantities, leading to useful statistical tools, including principal component analysis, linear dimension reduction, and analytical statistical modeling.
Journal ArticleDOI
Learning graph edit distance by graph neural networks
TL;DR: In this paper, the authors proposed a graph similarity learning framework based on geometric deep learning for graph retrieval and keyword spotting, which employs a message passing neural network to capture the graph structure and leverage this information for its use on a distance computation.
Book ChapterDOI
Improving Approximate Graph Edit Distance by Means of a Greedy Swap Strategy
Kaspar Riesen,Horst Bunke +1 more
TL;DR: A substantial gain of distance accuracy is empirically verified while run time is nearly not affected and an additional greedy search strategy is proposed that builds upon the initial assignment.
Journal ArticleDOI
Incremental Construction of Causal Network from News Articles
TL;DR: This work proposes the Topic-Event Causal model as a causal network model and an incremental constructing method based on it, which detects vertices representing similar events more precisely than conventional methods.
References
More filters
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.
Related Papers (5)
IAM Graph Database Repository for Graph Based Pattern Recognition and Machine Learning
Kaspar Riesen,Horst Bunke +1 more
A distance measure between attributed relational graphs for pattern recognition
Alberto Sanfeliu,King-Sun Fu +1 more