The core model which is considered in this paper is the neural gas model. This paper proposes an original hyperbolic visualization approach which is suitable to be applied on the results of such a model. The main principle of this approach is to use a hierarchical algorithm in order to summarize the gas contents in the form on a hypertree in which information on data density issued from the original neurons (i.e. clusters) description space is preserved. An application of this approach on a dataset of websites issued from European universities is presented in order to prove its accuracy.