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  Clustering Graphs by Weighted Substructure Mining

Tsuda, K., & Kudo, T. (2006). Clustering Graphs by Weighted Substructure Mining. In W. Cohen, & A. Moore (Eds.), ICML '06: Proceedings of the 23rd International Conference on Machine Learning (pp. 953-960). New York, NY, USA: ACM Press.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-D133-E Version Permalink: https://hdl.handle.net/21.11116/0000-0004-9A87-6
Genre: Conference Paper

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https://dl.acm.org/citation.cfm?doid=1143844.1143964 (Publisher version)
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 Creators:
Tsuda, K1, 2, Author           
Kudo, T, Author
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 is getting increasingly popular in, e.g., bioinformatics and text processing. 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 subgraphs, the dimensionality gets too large for usual statistical methods. We propose an efficient method for learning a binomial mixture model in this feature space. Combining the l1 regularizer and the data structure called DFS code tree, the MAP estimate of non-zero parameters are computed efficiently by means of the EM algorithm. Our method is applied to the clustering of RNA graphs, and is compared favorably with graph kernels and the spectral graph distance.

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 Dates: 2006-06
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1145/1143844.1143964
BibTex Citekey: 4068
 Degree: -

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Title: 23rd International Conference on Machine Learning (ICML 2006)
Place of Event: Pittsburgh, PA, USA
Start-/End Date: 2006-06-25 - 2006-06-29

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Title: ICML '06: Proceedings of the 23rd International Conference on Machine Learning
Source Genre: Proceedings
 Creator(s):
Cohen, W, Editor
Moore, A, Editor
Affiliations:
-
Publ. Info: New York, NY, USA : ACM Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 953 - 960 Identifier: ISBN: 1-59593-383-2