Traiter les Incohérences dans les Préférences (numériques) à l’aide de la Théorie des Possibilités

Gathering the preferences of a user in order to make correct recommendations becomes a difficult task when said user is uncertain of her choices. Using possibility theory as a means of modelling and detecting this uncertainty, we propose in this paper methods based on information fusion to make inferences despite observed inconsistencies due to user errors. While our approach is general, we illustrate its potential benefits on synthetic experiments using weighted averages as preference models.