The development of large ontologies for general and specific domains provides new tools to improve the quality of data mining techniques such as clustering. In this paper we explain how to improve clustering results by exploiting the semantics of categorical data by means of ontologies and how this semantics can be included into a hierarchical clustering method. We want to prove that when the conceptual meaning of the values is taken into account, it is possible to find a better interpretation of the clusters. This is demonstrated with the analysis of real data collected from visitors to of a Natural Reserve. The results of our methodology are compared with the ones obtained with a classical multivariate analysis done in the same database.

Peer Reviewed