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» Approximation Algorithms for Clustering Problems
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PR
2002
134views more  PR 2002»
15 years 4 months ago
Interactive clustering and merging with a new fuzzy expected value
7 Major problems exist in both crisp and fuzzy clustering algorithms. The fuzzy c-means type of algorithms use weights determined by a power m of inverse distances that remains
Carl G. Looney
VISSYM
2003
15 years 6 months ago
Adaptive Smooth Scattered Data Approximation for Large-scale Terrain Visualization
We present a fast method that adaptively approximates large-scale functional scattered data sets with hierarchical B-splines. The scheme is memory efficient, easy to implement an...
Martin Bertram, Xavier Tricoche, Hans Hagen
ICWS
2009
IEEE
16 years 2 months ago
What are the Problem Makers: Ranking Activities According to their Relevance for Process Changes
Recently, a new generation of adaptive process management technology has emerged, which enables dynamic changes of composite services and process models respectively. This, in tur...
Chen Li, Manfred Reichert, Andreas Wombacher
SDM
2009
SIAM
215views Data Mining» more  SDM 2009»
16 years 2 months ago
Hybrid Clustering of Text Mining and Bibliometrics Applied to Journal Sets.
To obtain correlated and complementary information contained in text mining and bibliometrics, hybrid clustering to incorporate textual content and citation information has become...
Bart De Moor, Frizo A. L. Janssens, Shi Yu, Wolfga...
ICDM
2005
IEEE
150views Data Mining» more  ICDM 2005»
15 years 10 months ago
Combining Multiple Clusterings by Soft Correspondence
Combining multiple clusterings arises in various important data mining scenarios. However, finding a consensus clustering from multiple clusterings is a challenging task because ...
Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu