103 search results - page 1 / 21 » Projective ART for clustering data sets in high dimensional ... |
NN
2002
Springer
13 years 4 months ago
2002
Springer
A new neural network architecture (PART) and the resulting algorithm are proposed to
SIGMOD
2000
ACM
13 years 9 months ago
2000
ACM
High dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Recent research results indicate that in high dimension...
VLDB
1999
ACM
1999
ACM
Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering
13 years 9 months ago
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...
PAKDD
2009
ACM
13 years 11 months ago
2009
ACM
Abstract. Clustering high dimensional data with sparse features is challenging because pairwise distances between data items are not informative in high dimensional space. To addre...
CORR
2010
Springer
13 years 5 months ago
2010
Springer
: Problem statement: Clustering has a number of techniques that have been developed in statistics, pattern recognition, data mining, and other fields. Subspace clustering enumerate...