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» Evaluation of Sampling for Data Mining of Association Rules
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KDD
2009
ACM
167views Data Mining» more  KDD 2009»
14 years 8 months ago
SNARE: a link analytic system for graph labeling and risk detection
Classifying nodes in networks is a task with a wide range of applications. It can be particularly useful in anomaly and fraud detection. Many resources are invested in the task of...
Mary McGlohon, Stephen Bay, Markus G. Anderle, Dav...
FLAIRS
2010
13 years 9 months ago
Handling of Numeric Ranges for Graph-Based Knowledge Discovery
Nowadays, graph-based knowledge discovery algorithms do not consider numeric attributes (they are discarded in the preprocessing step, or they are treated as alphanumeric values w...
Oscar E. Romero, Jesus A. Gonzalez, Lawrence B. Ho...
BMCBI
2006
154views more  BMCBI 2006»
13 years 7 months ago
Analysis with respect to instrumental variables for the exploration of microarray data structures
Background: Evaluating the importance of the different sources of variations is essential in microarray data experiments. Complex experimental designs generally include various fa...
Florent Baty, Michaël Facompré, Jan Wi...
BMCBI
2010
160views more  BMCBI 2010»
13 years 7 months ago
Extracting consistent knowledge from highly inconsistent cancer gene data sources
Background: Hundreds of genes that are causally implicated in oncogenesis have been found and collected in various databases. For efficient application of these abundant but diver...
Xue Gong, Ruihong Wu, Yuannv Zhang, Wenyuan Zhao, ...
KDD
2006
ACM
145views Data Mining» more  KDD 2006»
14 years 7 months ago
Deriving quantitative models for correlation clusters
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Arthur Zimek, Christian Böhm, Elke Achtert, H...