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» Comparisons Between Data Clustering Algorithms
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PAKDD
2009
ACM
123views Data Mining» more  PAKDD 2009»
14 years 8 days ago
Clustering with Lower Bound on Similarity
We propose a new method, called SimClus, for clustering with lower bound on similarity. Instead of accepting k the number of clusters to find, the alternative similarity-based app...
Mohammad Al Hasan, Saeed Salem, Benjarath Pupacdi,...
DIS
2006
Springer
13 years 11 months ago
On Class Visualisation for High Dimensional Data: Exploring Scientific Data Sets
Parametric Embedding (PE) has recently been proposed as a general-purpose algorithm for class visualisation. It takes class posteriors produced by a mixture-based clustering algori...
Ata Kabán, Jianyong Sun, Somak Raychaudhury...
BMCBI
2008
114views more  BMCBI 2008»
13 years 7 months ago
Visualizing and clustering high throughput sub-cellular localization imaging
Background: The expansion of automatic imaging technologies has created a need to be able to efficiently compare and review large sets of image data. To enable comparisons of imag...
Nicholas A. Hamilton, Rohan D. Teasdale
WWW
2010
ACM
14 years 2 months ago
Relational duality: unsupervised extraction of semantic relations between entities on the web
Extracting semantic relations among entities is an important first step in various tasks in Web mining and natural language processing such as information extraction, relation de...
Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuk...
PR
2008
169views more  PR 2008»
13 years 7 months ago
A survey of kernel and spectral methods for clustering
Clustering algorithms are a useful tool to explore data structures and have been employed in many disciplines. The focus of this paper is the partitioning clustering problem with ...
Maurizio Filippone, Francesco Camastra, Francesco ...