This paper proposes a semi-interactive system for visual data exploration using a clustering that combines an automatic approach with an interactive one. The user can manually perform the clustering, he can also choose to let the automated approach find optimal solutions and then interact with the process to improve the clustering results according to his visual perception and domain knowledge. The experiments show that the semi-interactive approach obtains better results than others.