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)
A new technique, SNIPER, is proposed for learning a model that deals with continuous values of exceptionality. Specifically, given some training objects associated with a continuous attribute <i>F</i>, SNIPER induces a rule-based model for the identification of those objects likely to score the maximum values for <i>F</i>. The purpose of SNIPER differs from(More)