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arXiv · 1411.0763

A Weighted Common Subgraph Matching Algorithm

Xu Yang·Hong Qiao·Zhi-Yong Liu
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Abstract

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 the equal-sized graph matching or subgraph matching, finds wide applications in many computer vision and machine learning tasks. In this paper, the 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 (GNCCP). Experimental comparisons on both synthetic graphs and real world images validate its robustness against noise level, problem size, outlier number, and edge density.

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Xu Yang, Hong Qiao, Zhi-Yong Liu. 2014-11-04. A Weighted Common Subgraph Matching Algorithm. https://arxiv.org/abs/1411.0763

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