Mobile computing adds a mostly unexplored dimension to data mining: user's position is a relevant piece of information, and recommendation systems, selecting and ranking links of interest to the user, have the opportunity to take location into account. In this paper, a mobility-aware recommendation system that considers the location of the user to filter recommended links is proposed. To avoid the potential problems and costs of insertion by hand, a new middleware layer, the location broker, maintains a historic database of locations and corresponding links used in the past and develops models relating resources to their spatial usage pattern. These models are used to calculate a preference metric when the current user is asking for resources of interest. Mobility scenarios are described and analyzed in terms of possible user requirements. The features of the PILGRIM mobile recommendation system are outlined together with a preliminary experimental evaluation of different metrics...