An Algorithm for Finding the Most Similar Given Sized Subgraphs in Two Weighted Graphs

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	An Algorithm for Finding the Most Similar Given Sized Subgraphs in Two Weighted Graphs
	Yang X(杨旭)
发表期刊	IEEE Transactions on Neural Networks and Learning Systems
	2017
期号	0 页码:0
摘要	We propose a weighted common subgraph (WCS) matching algorithm to find the most similar subgraphs in two labeled weighted graphs. WCS matching, as a natural generalization of equal-sized graph matching and subgraph matching, has found wide applications in many computer vision and machine learning tasks. In this brief, WCS matching is first formulated as a combinatorial optimization problem over the set of partial permutation matrices. Then, it is approximately solved by a recently proposed combinatorial optimization framework—graduated nonconvexity and concavity procedure. Experimental comparisons on both synthetic graphs and real-world images validate its robustness against noise level, problem size, outlier number, and edge density.
其他摘要	无
关键词	Graph Matching
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/15486
专题	多模态人工智能系统全国重点实验室_机器人理论与应用
推荐引用方式 GB/T 7714	Yang X. An Algorithm for Finding the Most Similar Given Sized Subgraphs in Two Weighted Graphs[J]. IEEE Transactions on Neural Networks and Learning Systems,2017(0):0.
APA	Yang X.(2017).An Algorithm for Finding the Most Similar Given Sized Subgraphs in Two Weighted Graphs.IEEE Transactions on Neural Networks and Learning Systems(0),0.
MLA	Yang X."An Algorithm for Finding the Most Similar Given Sized Subgraphs in Two Weighted Graphs".IEEE Transactions on Neural Networks and Learning Systems .0(2017):0.

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文件名称/大小	文献类型	版本类型	开放类型	使用许可
An Algorithm for Fin（737KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	浏览