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  Graph Mining with Variational Dirichlet Process Mixture Models

Tsuda, K. (2008). Graph Mining with Variational Dirichlet Process Mixture Models. In C. Apte, H. Park, K. Wang, & M. Zaki (Eds.), 8th SIAM International Conference on Data Mining 2008 (pp. 432-442). Philadelphia, PA, USA: Society for Industrial and Applied Mathematics.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-C9DD-B Version Permalink: http://hdl.handle.net/21.11116/0000-0003-7FC6-0
Genre: Conference Paper

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 Creators:
Tsuda, K1, 2, Author              
Zaki, MJ, Editor
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Graph data such as chemical compounds and XML documents are getting more common in many application domains. A main difficulty of graph data processing lies in the intrinsic high dimensionality of graphs, namely, when a graph is represented as a binary feature vector of indicators of all possible subgraph patterns, the dimensionality gets too large for usual statistical methods. We propose a nonparametric Bayesian method for clustering graphs and selecting salient patterns at the same time. Variational inference is adopted here, because sampling is not applicable due to extremely high dimensionality. The feature set minimizing the free energy is efficiently collected with the DFS code tree, where the generation of useless subgraphs is suppressed by a tree pruning condition. In experiments, our method is compared with a simpler approach based on frequent subgraph mining, and graph kernels.

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 Dates: 2008-04
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 4950
DOI: 10.1137/1.9781611972788.39
 Degree: -

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Title: 8th 2008 SIAM International Conference on Data Mining
Place of Event: Atlanta, GA, USA
Start-/End Date: 2008-04-24 - 2008-04-26

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Title: 8th SIAM International Conference on Data Mining 2008
Source Genre: Proceedings
 Creator(s):
Apte, C, Editor
Park, H, Editor
Wang, K, Editor
Zaki, MJ, Editor
Affiliations:
-
Publ. Info: Philadelphia, PA, USA : Society for Industrial and Applied Mathematics
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 432 - 442 Identifier: DOI: 10.1137/1.9781611972788