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» SPIN: mining maximal frequent subgraphs from graph databases
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SIGMOD
2008
ACM
215views Database» more  SIGMOD 2008»
14 years 5 months ago
CSV: visualizing and mining cohesive subgraphs
Extracting dense sub-components from graphs efficiently is an important objective in a wide range of application domains ranging from social network analysis to biological network...
Nan Wang, Srinivasan Parthasarathy, Kian-Lee Tan, ...
SDM
2009
SIAM
157views Data Mining» more  SDM 2009»
14 years 2 months ago
MUSK: Uniform Sampling of k Maximal Patterns.
Recent research in frequent pattern mining (FPM) has shifted from obtaining the complete set of frequent patterns to generating only a representative (summary) subset of frequent ...
Mohammad Al Hasan, Mohammed Javeed Zaki
RECOMB
2004
Springer
14 years 5 months ago
Mining protein family specific residue packing patterns from protein structure graphs
Finding recurring residue packing patterns, or spatial motifs, that characterize protein structural families is an important problem in bioinformatics. To this end, we apply a nov...
Jun Huan, Wei Wang 0010, Deepak Bandyopadhyay, Jac...
CIKM
2008
Springer
13 years 7 months ago
Structure feature selection for graph classification
With the development of highly efficient graph data collection technology in many application fields, classification of graph data emerges as an important topic in the data mining...
Hongliang Fei, Jun Huan
CIDM
2009
IEEE
13 years 9 months ago
Empirical comparison of graph classification algorithms
The graph classification problem is learning to classify separate, individual graphs in a graph database into two or more categories. A number of algorithms have been introduced fo...
Nikhil S. Ketkar, Lawrence B. Holder, Diane J. Coo...