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» Mining Very Large Databases
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VLDB
1998
ACM
192views Database» more  VLDB 1998»
14 years 2 months ago
Algorithms for Mining Distance-Based Outliers in Large Datasets
This paper deals with finding outliers (exceptions) in large, multidimensional datasets. The identification of outliers can lead to the discovery of truly unexpected knowledge in ...
Edwin M. Knorr, Raymond T. Ng
CIBCB
2008
IEEE
14 years 4 months ago
Very large scale ReliefF for genome-wide association analysis
— The genetic causes of many monogenic diseases have already been discovered. However, most common diseases are actually the result of complex nonlinear interactions between mult...
Margaret J. Eppstein, Paul Haake
VLDB
2004
ACM
245views Database» more  VLDB 2004»
14 years 3 months ago
VizTree: a Tool for Visually Mining and Monitoring Massive Time Series Databases
Moments before the launch of every space vehicle, engineering discipline specialists must make a critical go/no-go decision. The cost of a false positive, allowing a launch in spi...
Jessica Lin, Eamonn J. Keogh, Stefano Lonardi, Jef...
KDD
1995
ACM
129views Data Mining» more  KDD 1995»
14 years 1 months ago
Feature Extraction for Massive Data Mining
Techniques for learning from data typically require data to be in standard form. Measurements must be encoded in a numerical format such as binary true-or-false features, numerica...
V. Seshadri, Raguram Sasisekharan, Sholom M. Weiss
SIGMOD
2004
ACM
92views Database» more  SIGMOD 2004»
14 years 10 months ago
Online Maintenance of Very Large Random Samples
Random sampling is one of the most fundamental data management tools available. However, most current research involving sampling considers the problem of how to use a sample, and...
Chris Jermaine, Abhijit Pol, Subramanian Arumugam