Massimo Guarascio

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This paper presents a probabilistic co-clustering approach to pattern discovery in preference data. We extended the original formulation of the block mixture model to handle rating data, the resulting model allows the simultaneous clustering of users and items in homogeneous user communities and item categories. The parameter of the model are determined(More)
Monitoring the performances of a business process is a key issue in many organizations, especially when predefined constraints exist on them, due to contracts or internal requirements. Several approaches were defined recently in the literature for predicting the performances of a single process instance. However, in many real situations, process-oriented(More)