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» Approximate data mining in very large relational data
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TSDM
2000
151views Data Mining» more  TSDM 2000»
13 years 11 months ago
Rough Sets in Spatio-temporal Data Mining
In this paper I define spatio-temporal regions as pairs consisting of a spatial and a temporal component and I define topological relations between them. Using the notion of rough ...
Thomas Bittner
CIBCB
2008
IEEE
14 years 1 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
SEMWEB
2010
Springer
13 years 5 months ago
Optimize First, Buy Later: Analyzing Metrics to Ramp-Up Very Large Knowledge Bases
As knowledge bases move into the landscape of larger ontologies and have terabytes of related data, we must work on optimizing the performance of our tools. We are easily tempted t...
Paea LePendu, Natalya Fridman Noy, Clement Jonquet...
KAIS
2000
87views more  KAIS 2000»
13 years 7 months ago
An Index Structure for Data Mining and Clustering
Abstract. In this paper we present an index structure, called MetricMap, that takes a set of objects and a distance metric and then maps those objects to a k-dimensional space in s...
Xiong Wang, Jason Tsong-Li Wang, King-Ip Lin, Denn...
KDD
2002
ACM
155views Data Mining» more  KDD 2002»
14 years 7 months ago
SyMP: an efficient clustering approach to identify clusters of arbitrary shapes in large data sets
We propose a new clustering algorithm, called SyMP, which is based on synchronization of pulse-coupled oscillators. SyMP represents each data point by an Integrate-and-Fire oscill...
Hichem Frigui