Connectionist approach for Website visitors behaviors mining

Proposes 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 those 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 relates them to the winning neuron. Using this new version, we obtained a clustering of Web site visitors´ behaviors, which has been difficult to analyse before. This clustering allows a recommendation system to satisfy the Web site visitors´ needs based on their cluster membership at each step in time