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» An Extension of Self-organizing Maps to Categorical Data
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EPIA
2005
Springer
13 years 10 months ago
An Extension of Self-organizing Maps to Categorical Data
Self-organizing maps (SOM) have been recognized as a powerful tool in data exploratoration, especially for the tasks of clustering on high dimensional data. However, clustering on ...
Ning Chen, Nuno C. Marques
NN
2006
Springer
113views Neural Networks» more  NN 2006»
13 years 4 months ago
Large-scale data exploration with the hierarchically growing hyperbolic SOM
We introduce the Hierarchically Growing Hyperbolic Self-Organizing Map (H2 SOM) featuring two extensions of the HSOM (hyperbolic SOM): (i) a hierarchically growing variant that al...
Jörg Ontrup, Helge Ritter
ICDM
2003
IEEE
101views Data Mining» more  ICDM 2003»
13 years 10 months ago
Interactive Visualization and Navigation in Large Data Collections using the Hyperbolic Space
We propose the combination of two recently introduced methods for the interactive visual data mining of large collections of data. Both, Hyperbolic Multi-Dimensional Scaling (HMDS...
Jörg A. Walter, Jörg Ontrup, Daniel Wess...
KI
2007
Springer
13 years 11 months ago
Relational Neural Gas
Abstract. Prototype-based clustering algorithms such as the Self Organizing Map (SOM) or Neural Gas (NG) offer powerful tools for automated data inspection. The distribution of pr...
Barbara Hammer, Alexander Hasenfuss
LREC
2008
253views Education» more  LREC 2008»
13 years 6 months ago
Learning properties of Noun Phrases: from data to functions
The paper presents two experiments of unsupervised classification of Italian noun phrases. The goal of the experiments is to identify the most prominent contextual properties that...
Valeria Quochi, Basilio Calderone