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KDD
2005
ACM
162views Data Mining» more  KDD 2005»
15 years 10 months ago
Discovering frequent topological structures from graph datasets
The problem of finding frequent patterns from graph-based datasets is an important one that finds applications in drug discovery, protein structure analysis, XML querying, and soc...
Ruoming Jin, Chao Wang, Dmitrii Polshakov, Sriniva...
ICDM
2006
IEEE
147views Data Mining» more  ICDM 2006»
15 years 3 months ago
Adaptive Parallel Graph Mining for CMP Architectures
Mining graph data is an increasingly popular challenge, which has practical applications in many areas, including molecular substructure discovery, web link analysis, fraud detect...
Gregory Buehrer, Srinivasan Parthasarathy, Yen-Kua...
AAAI
2011
13 years 9 months ago
Relational Blocking for Causal Discovery
Blocking is a technique commonly used in manual statistical analysis to account for confounding variables. However, blocking is not currently used in automated learning algorithms...
Matthew J. Rattigan, Marc E. Maier, David Jensen
CHI
2006
ACM
15 years 10 months ago
GUESS: a language and interface for graph exploration
As graph models are applied to more widely varying fields, researchers struggle with tools for exploring and analyzing these structures. We describe GUESS, a novel system for grap...
Eytan Adar
ICPP
2009
IEEE
15 years 4 months ago
Generalizing k-Betweenness Centrality Using Short Paths and a Parallel Multithreaded Implementation
We present a new parallel algorithm that extends and generalizes the traditional graph analysis metric of betweenness centrality to include additional non-shortest paths according...
Karl Jiang, David Ediger, David A. Bader