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ICDM
2005
IEEE
138views Data Mining» more  ICDM 2005»
16 years 28 days ago
Labeling Unclustered Categorical Data into Clusters Based on the Important Attribute Values
Sampling has been recognized as an important technique to improve the efficiency of clustering. However, with sampling applied, those points which are not sampled will not have t...
Hung-Leng Chen, Kun-Ta Chuang, Ming-Syan Chen
MSS
2003
IEEE
108views Hardware» more  MSS 2003»
16 years 17 days ago
Effective Management of Hierarchical Storage Using Two Levels of Data Clustering
When data resides on tertiary storage, clustering is the key to achieving high retrieval performance. However, a straightforward approach to clustering massive amounts of data on ...
Ratko Orlandic
ECCV
2010
Springer
15 years 9 months ago
Clustering Complex Data with Group-Dependent Feature Selection
Abstract. We describe a clustering approach with the emphasis on detecting coherent structures in a complex dataset, and illustrate its effectiveness with computer vision applicat...
PR
2006
141views more  PR 2006»
15 years 7 months ago
Relaxational metric adaptation and its application to semi-supervised clustering and content-based image retrieval
The performance of many supervised and unsupervised learning algorithms is very sensitive to the choice of an appropriate distance metric. Previous work in metric learning and ada...
Hong Chang, Dit-Yan Yeung, William K. Cheung
ICML
2009
IEEE
16 years 8 months ago
Multi-assignment clustering for Boolean data
Conventional clustering methods typically assume that each data item belongs to a single cluster. This assumption does not hold in general. In order to overcome this limitation, w...
Andreas P. Streich, Mario Frank, David A. Basin, J...