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...
ITNG
2010
IEEE
13 years 10 months ago
2010
IEEE
— Clustering is a pivotal building block in many data mining applications and in machine learning in general. Most clustering algorithms in the literature pertain to off-line (or...
ICDM
2006
IEEE
13 years 11 months ago
2006
IEEE
Most clustering algorithms are partitional in nature, assigning each data point to exactly one cluster. However, several real world datasets have inherently overlapping clusters i...
ICDM
2006
IEEE
13 years 11 months ago
2006
IEEE
Clustering is ill-defined. Unlike supervised learning where labels lead to crisp performance criteria such as accuracy and squared error, clustering quality depends on how the cl...
ICPR
2008
IEEE
13 years 11 months ago
2008
IEEE
Most clustering algorithms operate by optimizing (either implicitly or explicitly) a single measure of cluster solution quality. Such methods may perform well on some data sets bu...
KDD
2006
ACM
14 years 5 months ago
2006
ACM
How do we find a natural clustering of a real world point set, which contains an unknown number of clusters with different shapes, and which may be contaminated by noise? Most clu...