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» Comparisons Between Data Clustering Algorithms
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CEC
2005
IEEE
14 years 1 months ago
Multiobjective clustering around medoids
Abstract- The large majority of existing clustering algorithms are centered around the notion of a feature, that is, individual data items are represented by their intrinsic proper...
Julia Handl, Joshua D. Knowles
KDD
2012
ACM
247views Data Mining» more  KDD 2012»
11 years 10 months ago
Integrating meta-path selection with user-guided object clustering in heterogeneous information networks
Real-world, multiple-typed objects are often interconnected, forming heterogeneous information networks. A major challenge for link-based clustering in such networks is its potent...
Yizhou Sun, Brandon Norick, Jiawei Han, Xifeng Yan...
SDM
2004
SIAM
212views Data Mining» more  SDM 2004»
13 years 9 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...
ICDM
2009
IEEE
130views Data Mining» more  ICDM 2009»
13 years 5 months ago
Efficient Anonymizations with Enhanced Utility
The k-anonymization method is a commonly used privacy-preserving technique. Previous studies used various measures of utility that aim at enhancing the correlation between the orig...
Jacob Goldberger, Tamir Tassa
APVIS
2010
13 years 9 months ago
Motion track: Visualizing variations of human motion data
This paper proposes a novel visualization approach, which can depict the variations between different human motion data. This is achieved by representing the time dimension of eac...
Yueqi Hu, Shuangyuan Wu, Shihong Xia, Jinghua Fu, ...