Abstract: In this paper, we propose a new version of the topological maps algorithm, which has been used to cluster web site visitors. These are characterized by partially redundant variables over time. In this version, we only consider the input vectors neurons that participate in the selection of the winning neuron in the map. In order to identify these neurons, we use a binary function. Subsequently, we apply a partial modification on the weights that relate them to the winning neuron. Using this new version, we obtained a clustering of web site visitors behavior, which has been difficult to analyze before. This clustering will allow a recommendation system to satisfy the web site visitor needs based on his cluster membership at each step in time.