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» Efficient Discovery of Confounders in Large Data Sets
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GI
1998
Springer
15 years 10 months ago
Self-Organizing Data Mining
"KnowledgeMiner" was designed to support the knowledge extraction process on a highly automated level. Implemented are 3 different GMDH-type self-organizing modeling algo...
Frank Lemke, Johann-Adolf Müller
IEAAIE
2005
Springer
15 years 11 months ago
Analyzing Multi-level Spatial Association Rules Through a Graph-Based Visualization
Association rules discovery is a fundamental task in spatial data mining where data are naturally described at multiple levels of granularity. ARES is a spatial data mining system ...
Annalisa Appice, Paolo Buono
BMCBI
2005
100views more  BMCBI 2005»
15 years 6 months ago
Speeding disease gene discovery by sequence based candidate prioritization
Background: Regions of interest identified through genetic linkage studies regularly exceed 30 centimorgans in size and can contain hundreds of genes. Traditionally this number is...
Euan A. Adie, Richard R. Adams, Kathryn L. Evans, ...
IS
2006
15 years 6 months ago
High dimensional nearest neighbor searching
As databases increasingly integrate different types of information such as time-series, multimedia and scientific data, it becomes necessary to support efficient retrieval of mult...
Hakan Ferhatosmanoglu, Ertem Tuncel, Divyakant Agr...
APWEB
2010
Springer
15 years 9 months ago
Computing Large Skylines over Few Dimensions: The Curse of Anti-correlation
The skyline of a set P of multi-dimensional points (tuples) consists of those points in P for which no clearly better point in P exists, using component-wise comparison on domains ...
Henning Köhler, Jing Yang