1. Arnoux, M., Lechevallier, Y., Tanasa, D., Trousse, B., and Verde, R. (2003). “Automatic Clustering for Web Usage Mining,” in Proceeding of SYNASC-2003-5th International Workshop on Symbolic and Numeric Algorithms for Scientific Computing, Timisoara, 1-4 October.
2. Bock, H.-H., and Diday, E. (eds.), (1999). Analysis of Symbolic Data, Exploratory Methods for Extracting Statistical Information from Complex Data, Springer-Verlag, Berlin.
3. Celeux, G., Diday, E., Govaert, G., Lechevallier, Y., and Ralambondrainy, H. (1989). Classification Automatique des Données, Bordas, Paris.
4. Chavent, M. (1997): Analyse des Données Symboliques. Une Méthode Divisive de Classification. Thèse de l’Université de PARIS-IX Dauphine.
5. Chavent, M., De Carvalho, F. A. T., and Lechevallier, Y. (2002): Dynamical Clustering of interval data. Optimization of an adequacy criterion based on Hausdorff distance, In: Classification, Clustering and Data Analysis, K. Jaguga et al. (Eds.), Springer, 53–60