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» An Approach to Clustering Abstracts
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CLUSTER
2004
IEEE
15 years 11 months ago
Cluster computing environment supporting single system image
Single system image(SSI) systems have been the mainstay of high-performance computing for many years. SSI requires the integration and aggregation of all types of resources in a c...
Min Choi, DaeWoo Lee, Seung Ryoul Maeng
SDM
2007
SIAM
122views Data Mining» more  SDM 2007»
15 years 8 months ago
Incremental Spectral Clustering With Application to Monitoring of Evolving Blog Communities
In recent years, spectral clustering method has gained attentions because of its superior performance compared to other traditional clustering algorithms such as K-means algorithm...
Huazhong Ning, Wei Xu, Yun Chi, Yihong Gong, Thoma...
SDM
2004
SIAM
212views Data Mining» more  SDM 2004»
15 years 8 months ago
Clustering with Bregman Divergences
A wide variety of distortion functions, such as squared Euclidean distance, Mahalanobis distance, Itakura-Saito distance and relative entropy, have been used for clustering. In th...
Arindam Banerjee, Srujana Merugu, Inderjit S. Dhil...
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
15 years 8 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar
SADM
2010
141views more  SADM 2010»
15 years 2 months ago
A parametric mixture model for clustering multivariate binary data
: The traditional latent class analysis (LCA) uses a mixture model with binary responses on each subject that are independent conditional on cluster membership. However, in many pr...
Ajit C. Tamhane, Dingxi Qiu, Bruce E. Ankenman