Modeling the Propagation of User Preferences

Abstract. User preferences are a fundamental ingredient of personalized database applications, in particular those in which the user context plays a key role. Given a set of preferences defined in different contexts, in this paper we study the problem of deriving the preferences that hold in one of them, that is, how preferences propagate through contexts. For the sake of generality, we work with an abstract context model, which only requires that the contexts form a poset. We first formalize the basic properties of the propagation process: specificity, stating that more specific contexts prevail on less specific ones, and fairness, stating that this behavior does not hold for incomparable contexts. We then introduce an algebraic model for preference propagation that relies on two well-known operators for combining preferences: Pareto and Prioritized composition. We study three alternative propagation methods and precisely characterize them in terms of the fairness and specificity properties.