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TKDE
2002
168views more  TKDE 2002»
13 years 7 months ago
CLARANS: A Method for Clustering Objects for Spatial Data Mining
Spatial data mining is the discovery of interesting relationships and characteristics that may exist implicitly in spatial databases. To this end, this paper has three main contrib...
Raymond T. Ng, Jiawei Han
SIGKDD
2000
95views more  SIGKDD 2000»
13 years 7 months ago
Scalability for Clustering Algorithms Revisited
This paper presents a simple new algorithm that performs k-means clustering in one scan of a dataset, while using a bu er for points from the dataset of xed size. Experiments show...
Fredrik Farnstrom, James Lewis, Charles Elkan
ICPADS
2005
IEEE
14 years 1 months ago
A Configurable Time-Controlled Clustering Algorithm for Wireless Sensor Networks
Future large-scale sensor networks may comprise thousands of wirelessly connected sensor nodes that could provide an unimaginable opportunity to interact with physical phenomena i...
S. Selvakennedy, Sukunesan Sinnappan
ALMOB
2006
109views more  ALMOB 2006»
13 years 8 months ago
A novel functional module detection algorithm for protein-protein interaction networks
Background: The sparse connectivity of protein-protein interaction data sets makes identification of functional modules challenging. The purpose of this study is to critically eva...
Woochang Hwang, Young-Rae Cho, Aidong Zhang, Mural...
CVPR
2008
IEEE
14 years 10 months ago
Generalised blurring mean-shift algorithms for nonparametric clustering
Gaussian blurring mean-shift (GBMS) is a nonparametric clustering algorithm, having a single bandwidth parameter that controls the number of clusters. The algorithm iteratively sh...
Miguel Á. Carreira-Perpiñán