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SIGMOD
1998
ACM
233views Database» more  SIGMOD 1998»
15 years 9 months ago
Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications
Data mining applications place special requirements on clustering algorithms including: the ability to nd clusters embedded in subspaces of high dimensional data, scalability, end...
Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopul...
149
Voted
FGCS
2008
148views more  FGCS 2008»
15 years 5 months ago
Grid-enabling data mining applications with DataMiningGrid: An architectural perspective
The DataMiningGrid system has been designed to meet the requirements of modern and distributed data mining scenarios. Based on the Globus Toolkit and other open technology and sta...
Vlado Stankovski, Martin T. Swain, Valentin Kravts...
MOBIDE
2010
ACM
15 years 5 months ago
Using data mining to handle missing data in multi-hop sensor network applications
A sensor's data loss or corruption, aka sensor data missing, is a common phenomenon in modern wireless sensor networks. It is more severe for multi-hop sensor network (MSN) a...
Le Gruenwald, Hanqing Yang, Md. Shiblee Sadik, Rah...
BMCBI
2004
161views more  BMCBI 2004»
15 years 5 months ago
Three-parameter lognormal distribution ubiquitously found in cDNA microarray data and its application to parametric data treatme
Background: To cancel experimental variations, microarray data must be normalized prior to analysis. Where an appropriate model for statistical data distribution is available, a p...
Tomokazu Konishi
SAC
2006
ACM
15 years 11 months ago
Discretization from data streams: applications to histograms and data mining
Abstract. In this paper we propose a new method to perform incremental discretization. The basic idea is to perform the task in two layers. The first layer receives the sequence o...
João Gama, Carlos Pinto