371 search results - page 3 / 75 » Learning to match and cluster large high-dimensional data se... |
IS
2006
13 years 7 months ago
2006
As databases increasingly integrate different types of information such as time-series, multimedia and scientific data, it becomes necessary to support efficient retrieval of mult...
PAMI
2010
13 years 6 months ago
2010
—This paper considers feature selection for data classification in the presence of a huge number of irrelevant features. We propose a new feature selection algorithm that addres...
SDM
2009
SIAM
14 years 4 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 ...
SIGMOD
2000
ACM
13 years 12 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...
PAKDD
2009
ACM
14 years 2 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...