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» Towards proximity pattern mining in large graphs
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PKDD
2010
Springer
155views Data Mining» more  PKDD 2010»
13 years 6 months ago
Latent Structure Pattern Mining
Pattern mining methods for graph data have largely been restricted to ground features, such as frequent or correlated subgraphs. Kazius et al. have demonstrated the use of elaborat...
Andreas Maunz, Christoph Helma, Tobias Cramer, Ste...
KDD
2006
ACM
164views Data Mining» more  KDD 2006»
14 years 8 months ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos
ICDM
2010
IEEE
158views Data Mining» more  ICDM 2010»
13 years 5 months ago
Patterns on the Connected Components of Terabyte-Scale Graphs
How do connected components evolve? What are the regularities that govern the dynamic growth process and the static snapshot of the connected components? In this work, we study pat...
U. Kang, Mary McGlohon, Leman Akoglu, Christos Fal...
SDM
2007
SIAM
143views Data Mining» more  SDM 2007»
13 years 9 months ago
Less is More: Compact Matrix Decomposition for Large Sparse Graphs
Given a large sparse graph, how can we find patterns and anomalies? Several important applications can be modeled as large sparse graphs, e.g., network traffic monitoring, resea...
Jimeng Sun, Yinglian Xie, Hui Zhang, Christos Falo...
ALMOB
2007
170views more  ALMOB 2007»
13 years 7 months ago
A spatio-temporal mining approach towards summarizing and analyzing protein folding trajectories
Understanding the protein folding mechanism remains a grand challenge in structural biology. In the past several years, computational theories in molecular dynamics have been empl...
Hui Yang, Srinivasan Parthasarathy, Duygu Ucar