21 search results - page 2 / 5 » GESS: a scalable similarity-join algorithm for mining large ... |
SDM
2009
SIAM
14 years 2 months ago
2009
SIAM
Subspace clustering and frequent itemset mining via “stepby-step” algorithms that search the subspace/pattern lattice in a top-down or bottom-up fashion do not scale to large ...
ICPP
2000
IEEE
13 years 9 months ago
2000
IEEE
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
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...
BTW
2009
Springer
13 years 6 months ago
2009
Springer
Abstract: Multimedia databases are increasingly common in science, business, entertainment and many other applications. Their size and high dimensionality of features are major cha...
KDD
2004
ACM
14 years 5 months ago
2004
ACM
The computation of covariance and correlation matrices are critical to many data mining applications and processes. Unfortunately the classical covariance and correlation matrices...