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ESANN
2008
15 years 1 months ago
Parallelizing single patch pass clustering
Clustering algorithms such as k-means, the self-organizing map (SOM), or Neural Gas (NG) constitute popular tools for automated information analysis. Since data sets are becoming l...
Nikolai Alex, Barbara Hammer
EDM
2010
129views Data Mining» more  EDM 2010»
15 years 1 months ago
Skill Set Profile Clustering: The Empty K-Means Algorithm with Automatic Specification of Starting Cluster Centers
While students' skill set profiles can be estimated with formal cognitive diagnosis models [8], their computational complexity makes simpler proxy skill estimates attractive [...
Rebecca Nugent, Nema Dean, Elizabeth Ayers
IPPS
2010
IEEE
14 years 9 months ago
Large-scale multi-dimensional document clustering on GPU clusters
Document clustering plays an important role in data mining systems. Recently, a flocking-based document clustering algorithm has been proposed to solve the problem through simulat...
Yongpeng Zhang, Frank Mueller, Xiaohui Cui, Thomas...
CORR
1999
Springer
222views Education» more  CORR 1999»
14 years 11 months ago
Analysis of approximate nearest neighbor searching with clustered point sets
Abstract. Nearest neighbor searching is a fundamental computational problem. A set of n data points is given in real d-dimensional space, and the problem is to preprocess these poi...
Songrit Maneewongvatana, David M. Mount
PKDD
2000
Springer
144views Data Mining» more  PKDD 2000»
15 years 3 months ago
Fast Hierarchical Clustering Based on Compressed Data and OPTICS
: One way to scale up clustering algorithms is to squash the data by some intelligent compression technique and cluster only the compressed data records. Such compressed data recor...
Markus M. Breunig, Hans-Peter Kriegel, Jörg S...