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» Approximate data mining in very large relational data
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BMCBI
2006
170views more  BMCBI 2006»
15 years 1 months ago
Biclustering of gene expression data by non-smooth non-negative matrix factorization
Background: The extended use of microarray technologies has enabled the generation and accumulation of gene expression datasets that contain expression levels of thousands of gene...
Pedro Carmona-Saez, Roberto D. Pascual-Marqui, Fra...
ICDM
2005
IEEE
146views Data Mining» more  ICDM 2005»
15 years 7 months ago
Merging Interface Schemas on the Deep Web via Clustering Aggregation
We consider the problem of integrating a large number of interface schemas over the Deep Web, The scale of the problem and the diversity of the sources present serious challenges ...
Wensheng Wu, AnHai Doan, Clement T. Yu
FLAIRS
2008
15 years 4 months ago
Building Useful Models from Imbalanced Data with Sampling and Boosting
Building useful classification models can be a challenging endeavor, especially when training data is imbalanced. Class imbalance presents a problem when traditional classificatio...
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van H...
SDM
2009
SIAM
164views Data Mining» more  SDM 2009»
15 years 11 months ago
Exact Discovery of Time Series Motifs.
Time series motifs are pairs of individual time series, or subsequences of a longer time series, which are very similar to each other. As with their discrete analogues in computat...
Abdullah Mueen, Eamonn J. Keogh, M. Brandon Westov...
KDD
2010
ACM
188views Data Mining» more  KDD 2010»
15 years 3 months ago
Inferring networks of diffusion and influence
Information diffusion and virus propagation are fundamental processes talking place in networks. While it is often possible to directly observe when nodes become infected, observi...
Manuel Gomez-Rodriguez, Jure Leskovec, Andreas Kra...