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» Finding Spatial Patterns in Network Data
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ICML
2004
IEEE
16 years 3 months ago
Learning associative Markov networks
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
125
Voted
KDD
2005
ACM
162views Data Mining» more  KDD 2005»
16 years 2 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...
RECOMB
2004
Springer
16 years 2 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...
120
Voted
NBIS
2010
Springer
15 years 10 days ago
Mining Association Rules Consisting of Download Servers from Distributed Honeypot Observation
This paper aims to find interested association rules, known as data mining technique, out of the dataset of downloading logs by focusing on the coordinated activity among downloadi...
Masayuki Ohrui, Hiroaki Kikuchi, Masato Terada
SIGKDD
2008
125views more  SIGKDD 2008»
15 years 2 months ago
Incremental pattern discovery on streams, graphs and tensors
Incremental pattern discovery targets streaming applications where the data continuously arrive incrementally. The questions are how to find patterns (main trends) incrementally; ...
Jimeng Sun