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» Extracting Landmarks with Data Mining Methods
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KDD
1998
ACM
145views Data Mining» more  KDD 1998»
13 years 12 months ago
Coincidence Detection: A Fast Method for Discovering Higher-Order Correlations in Multidimensional Data
Wepresent a novel, fast methodfor associationminingill high-dimensionaldatasets. OurCoincidence Detection method, which combines random sampling and Chernoff-Hoeffding bounds with...
Evan W. Steeg, Derek A. Robinson, Ed Willis
ICDE
2006
IEEE
165views Database» more  ICDE 2006»
14 years 1 months ago
Privacy Preserving Clustering on Horizontally Partitioned Data
Data mining has been a popular research area for more than a decade due to its vast spectrum of applications. The power of data mining tools to extract hidden information that can...
Ali Inan, Yücel Saygin, Erkay Savas, Ay&ccedi...
DGO
2003
140views Education» more  DGO 2003»
13 years 9 months ago
Social Welfare Program Administration and Evaluation and Policy Analysis Using Knowledge Discovery and Data Mining (KDD) on Admi
New technology in knowledge discovery and data mining (KDD) make it possible to extract valuable information from operational data. Private businesses already use the technology f...
Hye-Chung (Monica) Kum, Dean Duncan, Kimberly Flai...
SIGKDD
2000
237views more  SIGKDD 2000»
13 years 7 months ago
The UCI KDD Archive of Large Data Sets for Data Mining Research and Experimentation
Advances in data collection and storage have allowed organizations to create massive, complex and heterogeneous databases, which have stymied traditional methods of data analysis....
Stephen D. Bay, Dennis F. Kibler, Michael J. Pazza...
BMCBI
2010
154views more  BMCBI 2010»
13 years 7 months ago
EnvMine: A text-mining system for the automatic extraction of contextual information
Background: For ecological studies, it is crucial to count on adequate descriptions of the environments and samples being studied. Such a description must be done in terms of thei...
Javier Tamames, Victor de Lorenzo