  In data analysis new forms of complex data have to be considered like for
example (symbolic data, functional data, web data, trees, SQL query and
multimedia data, ...). In this context classical data analysis for knowledge
discovery based on calculating the center of gravity can not be used because
input are not $\mathbb{R}^p$ vectors. In this paper, we present an application
on real world symbolic data using the self-organizing map. To this end, we
propose an extension of the self-organizing map that can handle symbolic data.
