Sciweavers

25041 search results - page 6 / 5009
» Algorithms for Clustering Data
Sort
View
IBPRIA
2003
Springer
14 years 1 months ago
Incrementally Assessing Cluster Tendencies with a Maximum Variance Cluster Algorithm
A straightforward and efficient way to discover clustering tendencies in data using a recently proposed Maximum Variance Clustering algorithm is proposed. The approach shares the ...
Krzysztof Rzadca, Francesc J. Ferri
BMVC
1998
13 years 9 months ago
A Method for Dynamic Clustering of Data
This paper describes a method for the segmentation of dynamic data. It extends well known algorithms developed in the context of static clustering (e.g., the c-means algorithm, Ko...
Arnaldo J. Abrantes, Jorge S. Marques
ICAI
2004
13 years 9 months ago
K-medoid-style Clustering Algorithms for Supervised Summary Generation
This paper centers on the discussion of k-medoid-style clustering algorithms for supervised summary generation. This task requires clustering techniques that identify class-unifor...
Nidal M. Zeidat, Christoph F. Eick
CEC
2008
IEEE
14 years 2 months ago
A Quantum-inspired Genetic Algorithm for data clustering
—The conventional K-Means clustering algorithm must know the number of clusters in advance and the clustering result is sensitive to the selection of the initial cluster centroid...
Jing Xiao, YuPing Yan, Ying Lin, Ling Yuan, Jun Zh...
SIGMOD
1998
ACM
233views Database» more  SIGMOD 1998»
14 years 3 days ago
Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications
Data mining applications place special requirements on clustering algorithms including: the ability to nd clusters embedded in subspaces of high dimensional data, scalability, end...
Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopul...