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KDD
2009
ACM
163views Data Mining» more  KDD 2009»
14 years 8 months ago
Large-scale graph mining using backbone refinement classes
We present a new approach to large-scale graph mining based on so-called backbone refinement classes. The method efficiently mines tree-shaped subgraph descriptors under minimum f...
Andreas Maunz, Christoph Helma, Stefan Kramer
IPPS
2008
IEEE
14 years 2 months ago
Parallel mining of closed quasi-cliques
Graph structure can model the relationships among a set of objects. Mining quasi-clique patterns from large dense graph data makes sense with respect to both statistic and applica...
Yuzhou Zhang, Jianyong Wang, Zhiping Zeng, Lizhu Z...
SDM
2008
SIAM
256views Data Mining» more  SDM 2008»
13 years 9 months ago
Graph Mining with Variational Dirichlet Process Mixture Models
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 ...
Koji Tsuda, Kenichi Kurihara
SDM
2010
SIAM
213views Data Mining» more  SDM 2010»
13 years 9 months ago
Spectral Analysis of Signed Graphs for Clustering, Prediction and Visualization
We study the application of spectral clustering, prediction and visualization methods to graphs with negatively weighted edges. We show that several characteristic matrices of gra...
Jérôme Kunegis, Stephan Schmidt, Andr...
ICDM
2009
IEEE
197views Data Mining» more  ICDM 2009»
13 years 5 months ago
A Linear-Time Graph Kernel
The design of a good kernel is fundamental for knowledge discovery from graph-structured data. Existing graph kernels exploit only limited information about the graph structures bu...
Shohei Hido, Hisashi Kashima