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» CURE: An Efficient Clustering Algorithm for Large Databases
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KDD
1997
ACM
104views Data Mining» more  KDD 1997»
15 years 3 months ago
An Efficient Algorithm for the Incremental Updation of Association Rules in Large Databases
Efficient discover of association rules in large databases is a we 1 studied problem and several ap-1y proaches have been proposed. However, it is non trivial to maintain the asso...
Shiby Thomas, Sreenath Bodagala, Khaled Alsabti, S...
CORR
2010
Springer
145views Education» more  CORR 2010»
14 years 11 months ago
Feature Level Clustering of Large Biometric Database
This paper proposes an efficient technique for partitioning large biometric database during identification. In this technique feature vector which comprises of global and local de...
Hunny Mehrotra, Dakshina Ranjan Kisku, V. Bhawani ...
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BMCBI
2010
139views more  BMCBI 2010»
14 years 11 months ago
A highly efficient multi-core algorithm for clustering extremely large datasets
Background: In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput t...
Johann M. Kraus, Hans A. Kestler
EDBT
2004
ACM
192views Database» more  EDBT 2004»
15 years 11 months ago
LIMBO: Scalable Clustering of Categorical Data
Abstract. Clustering is a problem of great practical importance in numerous applications. The problem of clustering becomes more challenging when the data is categorical, that is, ...
Periklis Andritsos, Panayiotis Tsaparas, Ren&eacut...