Incorporating Discrete Constraints Into Random Walk-Based Graph Matching

Xu Yang; Zhi-Yong Liu; Hong Qiaoxu

doi:10.1109/tsmc.2017.2693029

Incorporating Discrete Constraints Into Random Walk-Based Graph Matching

IEEE Transactions on Systems Man and Cybernetics Systems ◽

10.1109/tsmc.2017.2693029 ◽

2020 ◽

Vol 50 (4) ◽

pp. 1406-1416 ◽

Cited By ~ 2

Author(s):

Xu Yang ◽

Zhi-Yong Liu ◽

Hong Qiaoxu

Keyword(s):

Random Walk ◽

Graph Matching

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Context-Dependent Random Walk Graph Kernels and Tree Pattern Graph Matching Kernels With Applications to Action Recognition

IEEE Transactions on Image Processing ◽

10.1109/tip.2018.2849885 ◽

2018 ◽

Vol 27 (10) ◽

pp. 5060-5075 ◽

Cited By ~ 5

Author(s):

Weiming Hu ◽

Baoxin Wu ◽

Pei Wang ◽

Chunfeng Yuan ◽

Yangxi Li ◽

...

Keyword(s):

Random Walk ◽

Action Recognition ◽

Graph Matching ◽

Graph Kernels ◽

Tree Pattern ◽

Context Dependent ◽

Pattern Graph

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STRING EDIT DISTANCE, RANDOM WALKS AND GRAPH MATCHING

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001404003277 ◽

2004 ◽

Vol 18 (03) ◽

pp. 315-327 ◽

Cited By ~ 33

Author(s):

ANTONIO ROBLES-KELLY ◽

EDWIN R. HANCOCK

Keyword(s):

Markov Chain ◽

Random Walk ◽

Steady State ◽

Adjacency Matrix ◽

Transition Matrix ◽

Edit Distance ◽

Graph Matching ◽

Transition Probability ◽

Transition Probability Matrix ◽

String Edit Distance

This paper shows how the eigenstructure of the adjacency matrix can be used for the purposes of robust graph matching. We commence from the observation that the leading eigenvector of a transition probability matrix is the steady state of the associated Markov chain. When the transition matrix is the normalized adjacency matrix of a graph, then the leading eigenvector gives the sequence of nodes of the steady state random walk on the graph. We use this property to convert the nodes in a graph into a string where the node-order is given by the sequence of nodes visited in the random walk. We match graphs represented in this way, by finding the sequence of string edit operations which minimize edit distance.

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Research on Random Walk Rough Matching Algorithm of Attribute Sub-Graph

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.474-476.297 ◽

2011 ◽

Vol 474-476 ◽

pp. 297-302

Author(s):

Chun Ying Zhang ◽

Jing Feng Guo ◽

Xiao Chen

Keyword(s):

Social Network ◽

Random Walk ◽

Graph Matching ◽

Matching Problem ◽

Matching Algorithm

In the analysis of social network, the attribute values of an entity change constantly as time goes by and the corresponding attribute graph changes accordingly. However, the essence of the entity is invariable. The problem is how to discover essence from the change of mining frequent rough matching attribute sub-graph in an attribute graph in this paper. The problem of the attribute sub-graph rough matching is defined and described, then the random walk rough matching algorithm of attribute sub-graph is designed so that the problem of incomplete coincide attribute sub-graph rough matching would be solved. Attribute sub-graph is the expansion of the traditional sub-graph; rough matching problem is the extension of traditional sub-graph matching problem. With the help of the random walk rough matching algorithm of attribute sub-graph, more potential frequent attribute sub-graphs can be discovered, and more valuable information mined.

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