Recurrent Self-Organizing Map (RSOM) is studied in three di erent time series prediction cases. RSOM is used to cluster the series into local data sets, for which corresponding lo...
Timo Koskela, Markus Varsta, Jukka Heikkonen, Kimm...
: There is a long tradition of describing cities through a focus on the characteristics of their residents. A brief review of the history of this approach to describing cities high...
The Generative Topographic Mapping (GTM) was originally conceived as a probabilistic alternative to the well-known, neural networkinspired, Self-Organizing Maps. The GTM can also ...
Abstract. In order to explore the social organization of a medieval peasant community before the Hundred Years’ War, we propose the use of an adaptation of the well-known Kohonen...
Text clustering is one of the difficult and hot research fields in the text mining research. Combing Map Reduce framework and the neuron initialization method of VPSOM (vector pre...