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VLDB
1999
ACM
224views Database» more  VLDB 1999»
13 years 9 months ago
Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering
Many applications require the clustering of large amounts of high-dimensional data. Most clustering algorithms, however, do not work e ectively and e ciently in highdimensional sp...
Alexander Hinneburg, Daniel A. Keim
DMIN
2008
152views Data Mining» more  DMIN 2008»
13 years 6 months ago
PCS: An Efficient Clustering Method for High-Dimensional Data
Clustering algorithms play an important role in data analysis and information retrieval. How to obtain a clustering for a large set of highdimensional data suitable for database ap...
Wei Li 0011, Cindy Chen, Jie Wang
KDD
2007
ACM
231views Data Mining» more  KDD 2007»
14 years 5 months ago
Xproj: a framework for projected structural clustering of xml documents
XML has become a popular method of data representation both on the web and in databases in recent years. One of the reasons for the popularity of XML has been its ability to encod...
Charu C. Aggarwal, Na Ta, Jianyong Wang, Jianhua F...
DIS
2006
Springer
13 years 8 months ago
On Class Visualisation for High Dimensional Data: Exploring Scientific Data Sets
Parametric Embedding (PE) has recently been proposed as a general-purpose algorithm for class visualisation. It takes class posteriors produced by a mixture-based clustering algori...
Ata Kabán, Jianyong Sun, Somak Raychaudhury...
ICDE
2009
IEEE
171views Database» more  ICDE 2009»
14 years 6 months ago
A Framework for Clustering Massive-Domain Data Streams
In this paper, we will examine the problem of clustering massive domain data streams. Massive-domain data streams are those in which the number of possible domain values for each a...
Charu C. Aggarwal