Skip to Main Content
Skip Nav Destination
ASME Press Select Proceedings
International Conference on Computer Technology and Development, 3rd (ICCTD 2011)
By
Jianhong Zhou
Jianhong Zhou
Search for other works by this author on:
ISBN:
9780791859919
No. of Pages:
2000
Publisher:
ASME Press
Publication date:
2011

In this paper, we present a generative model to measure graph similarity. The parameters of that random process generating the observed graph from a template are determined by the node indices, reflecting the structure compatibility between nodes. We propose to use the steady state of the dynamic system represented by a directed graph to index the nodes. A message passing algorithm using the loopy belief propagation is adopted to approximate the maximum a posteriori assignment (MAP) for the nodes. The resulted believes of self matching form a similarity measure of the nodes in a graph. Examples and experiments demonstrated that the proposed method worked well for large graphs.

Abstract
Key Words
1 Introduction
2. Related Work
3 Proposed Algorithms
4.Empirical Evaluation
5.Conclusions
Acknowledgments
References
This content is only available via PDF.
You do not currently have access to this chapter.
Close Modal

or Create an Account

Close Modal
Close Modal