  The Kohonen algorithm (SOM, Kohonen,1984, 1995) is a very powerful tool for
data analysis. It was originally designed to model organized connections
between some biological neural networks. It was also immediately considered as
a very good algorithm to realize vectorial quantization, and at the same time
pertinent classification, with nice properties for visualization. If the
individuals are described by quantitative variables (ratios, frequencies,
measurements, amounts, etc.), the straightforward application of the original
algorithm leads to build code vectors and to associate to each of them the
class of all the individuals which are more similar to this code-vector than to
the others. But, in case of individuals described by categorical (qualitative)
variables having a finite number of modalities (like in a survey), it is
necessary to define a specific algorithm. In this paper, we present a new
algorithm inspired by the SOM algorithm, which provides a simultaneous
classification of the individuals and of their modalities.
