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» Mining Very Large Databases
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KDD
2002
ACM
166views Data Mining» more  KDD 2002»
14 years 10 months ago
Frequent term-based text clustering
Text clustering methods can be used to structure large sets of text or hypertext documents. The well-known methods of text clustering, however, do not really address the special p...
Florian Beil, Martin Ester, Xiaowei Xu
GECCO
2008
Springer
232views Optimization» more  GECCO 2008»
13 years 11 months ago
An efficient SVM-GA feature selection model for large healthcare databases
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...
DAWAK
2001
Springer
14 years 2 months ago
Determining the Convex Hull in Large Multidimensional Databases
Determiningthe convex hull ofa point set isa basic operation for many applications of pattern recognition, image processing, statistics, and data mining. Although the corresponding...
Christian Böhm, Hans-Peter Kriegel
FQAS
2004
Springer
146views Database» more  FQAS 2004»
14 years 1 months ago
Discovering Representative Models in Large Time Series Databases
The discovery of frequently occurring patterns in a time series could be important in several application contexts. As an example, the analysis of frequent patterns in biomedical ...
Simona E. Rombo, Giorgio Terracina
SDM
2009
SIAM
144views Data Mining» more  SDM 2009»
14 years 7 months ago
CORE: Nonparametric Clustering of Large Numeric Databases.
Current clustering techniques are able to identify arbitrarily shaped clusters in the presence of noise, but depend on carefully chosen model parameters. The choice of model param...
Andrej Taliun, Arturas Mazeika, Michael H. Bö...