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» On Weighting Clustering
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ICDM
2010
IEEE
230views Data Mining» more  ICDM 2010»
14 years 12 months ago
Clustering Large Attributed Graphs: An Efficient Incremental Approach
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
Yang Zhou, Hong Cheng, Jeffrey Xu Yu
101
Voted
CSDA
2007
115views more  CSDA 2007»
15 years 1 months ago
Arbitrarily shaped multiple spatial cluster detection for case event data
An original method is proposed for spatial cluster detection of case event data. A selection order and the distance from the nearest neighbour are attributed to each point, once p...
Christophe Dematteï, Nicolas Molinari, Jean-P...
107
Voted
SIGIR
2000
ACM
15 years 6 months ago
An investigation of linguistic features and clustering algorithms for topical document clustering
We investigate four hierarchical clustering methods (single-link, complete-link, groupwise-average, and single-pass) and two linguistically motivated text features (noun phrase he...
Vasileios Hatzivassiloglou, Luis Gravano, Ankineed...
ICPR
2010
IEEE
15 years 2 months ago
Improved Mean Shift Algorithm with Heterogeneous Node Weights
The conventional mean shift algorithm has been known to be sensitive to selecting a bandwidth. We present a robust mean shift algorithm with heterogeneous node weights that come f...
Ji Won Yoon, Simon P. Wilson
118
Voted
CIKM
2006
Springer
15 years 5 months ago
Multi-task text segmentation and alignment based on weighted mutual information
Text segmentation is important for text analysis, while text alignment is to determine shared sub-topics among similar documents. Multi-task text segmentation and alignment is the...
Bingjun Sun, Ding Zhou, Hongyuan Zha, John Yen