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» A Partition-Based Approach to Graph Mining
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CIKM
2011
Springer
12 years 6 months ago
Content based social behavior prediction: a multi-task learning approach
The study of information flow analyzes the principles and mechanisms of social information distribution. It is becoming an extremely important research topic in social network re...
Hongliang Fei, Ruoyi Jiang, Yuhao Yang, Bo Luo, Ju...
PKDD
2009
Springer
175views Data Mining» more  PKDD 2009»
14 years 1 months ago
Latent Dirichlet Bayesian Co-Clustering
Co-clustering has emerged as an important technique for mining contingency data matrices. However, almost all existing coclustering algorithms are hard partitioning, assigning each...
Pu Wang, Carlotta Domeniconi, Kathryn B. Laskey
ICTAI
2006
IEEE
14 years 23 days ago
Preserving Patterns in Bipartite Graph Partitioning
This paper describes a new bipartite formulation for word-document co-clustering such that hyperclique patterns, strongly affiliated documents in this case, are guaranteed not to ...
Tianming Hu, Chao Qu, Chew Lim Tan, Sam Yuan Sung,...
SDM
2009
SIAM
157views Data Mining» more  SDM 2009»
14 years 3 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
BMCBI
2008
149views more  BMCBI 2008»
13 years 6 months ago
All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning
Background: Automated extraction of protein-protein interactions (PPI) is an important and widely studied task in biomedical text mining. We propose a graph kernel based approach ...
Antti Airola, Sampo Pyysalo, Jari Björne, Tap...