A methodology for automatically identifying and clustering semantic features or topics in a heterogeneous text collection is presented. Textual data is encoded using a low rank no...
Farial Shahnaz, Michael W. Berry, V. Paul Pauca, R...
The Self-Organizing Map (SOM) is one of the popular Artificial Neural Networks which is a useful in clustering and visualizing complex high dimensional data. Conventional SOMs are...
In the paper, we analyze the software that realizes the self-organizing maps: SOM-PAK, SOM-TOOLBOX, Viscovery SOMine, Nenet, and two academic systems. Most of the software may be f...
— We propose here an analysis of a rich dataset which gives an exhaustive and dynamic view of the exchanges processed in a running eDonkey system. We focus on correlation in term...
Multi-dimensional spatial data are obtained when a number of data acquisition devices are deployed at different locations to measure a certain set of attributes of the study subje...