436 search results - page 12 / 88 » Automatic Subspace Clustering of High Dimensional Data for D... |
KDD
2000
ACM
13 years 11 months ago
2000
ACM
The grand tour, one of the most popular methods for multidimensional data exploration, is based on orthogonally projecting multidimensional data to a sequence of lower dimensional...
WIRN
2005
Springer
14 years 1 months ago
2005
Springer
We present an algorithmic scheme for unsupervised cluster ensembles, based on randomized projections between metric spaces, by which a substantial dimensionality reduction is obtai...
KDD
2001
ACM
14 years 8 months ago
2001
ACM
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
ISMIS
1999
Springer
13 years 12 months ago
1999
Springer
Knowledge Discovery in Databases (KDD) is a data analysis process which, in contrast to conventional data analysis, automatically generates and evaluates very many hypotheses, deal...
ICDE
2003
IEEE
14 years 9 months ago
2003
IEEE
The notorious "dimensionality curse" is a well-known phenomenon for any multi-dimensional indexes attempting to scale up to high dimensions. One well known approach to o...