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» Numbers in Multi-relational Data Mining
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BMCBI
2006
169views more  BMCBI 2006»
15 years 4 months ago
Finding biological process modifications in cancer tissues by mining gene expression correlations
Background: Through the use of DNA microarrays it is now possible to obtain quantitative measurements of the expression of thousands of genes from a biological sample. This techno...
Giacomo Gamberoni, Sergio Storari, Stefano Volinia
IMC
2010
ACM
15 years 2 months ago
What happened in my network: mining network events from router syslogs
Router syslogs are messages that a router logs to describe a wide range of events observed by it. They are considered one of the most valuable data sources for monitoring network ...
Tongqing Qiu, Zihui Ge, Dan Pei, Jia Wang, Jun Xu
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
13 years 7 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
KES
2004
Springer
15 years 10 months ago
FIT: A Fast Algorithm for Discovering Frequent Itemsets in Large Databases
Association rule mining is an important data mining problem that has been studied extensively. In this paper, a simple but Fast algorithm for Intersecting attribute lists using a ...
Jun Luo, Sanguthevar Rajasekaran
KDD
2008
ACM
140views Data Mining» more  KDD 2008»
16 years 5 months ago
Semi-supervised approach to rapid and reliable labeling of large data sets
Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...
György J. Simon, Vipin Kumar, Zhi-Li Zhang