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» CURE: An Efficient Clustering Algorithm for Large Databases
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KES
2004
Springer
15 years 5 months ago
FIT: A Fast Algorithm for Discovering Frequent Itemsets in Large Databases
Association rule mining is an important data mining problem that has been studied extensively. In this paper, a simple but Fast algorithm for Intersecting attribute lists using a ...
Jun Luo, Sanguthevar Rajasekaran
JSS
2007
67views more  JSS 2007»
14 years 11 months ago
TFRP: An efficient microaggregation algorithm for statistical disclosure control
Recently, the issue of Statistic Disclosure Control (SDC) has attracted much attention. SDC is a very important part of data security dealing with the protection of databases. Micr...
Chin-Chen Chang, Yu-Chiang Li, Wen-Hung Huang
PDCN
2004
15 years 1 months ago
K-Means VQ algorithm using a low-cost parallel cluster computing
It is well-known that the time and memory necessary to create a codebook from large training databases have hindered the vector quantization based systems for real applications. T...
Paulo Sergio Lopes de Souza, Alceu de Souza Britto...
BTW
2009
Springer
240views Database» more  BTW 2009»
15 years 24 days ago
Efficient Adaptive Retrieval and Mining in Large Multimedia Databases
Abstract: Multimedia databases are increasingly common in science, business, entertainment and many other applications. Their size and high dimensionality of features are major cha...
Ira Assent
EUROPAR
1999
Springer
15 years 4 months ago
Parallel k/h-Means Clustering for Large Data Sets
This paper describes the realization of a parallel version of the k/h-means clustering algorithm. This is one of the basic algorithms used in a wide range of data mining tasks. We ...
Kilian Stoffel, Abdelkader Belkoniene