Information access technologies, like information retrieval, information filtering and database management, aim at modelling, designing and implementing systems able to provide fast and effective content-based access to a large amount of multimedia information. The aim of these systems is to estimate the relevance of information items to a user's information need. This is a very hard and complex task, since it is pervaded with subjectivity, vagueness and uncertainty. Many existing systems offer only a simple modelling of the information access task, which often privileges efficiency at the expenses of expressiveness. Search engines are a clear example of this situation: many irrelevant documents are retrieved in response to a user query. The lack of expressiveness in both the user's formulation of their information needs and in the presentation of the results to the user, together with the extreme simplification of the document representation, has also detrimental effects on the system effectiveness, as perceived by the user. We believe that a promising direction to improve effectiveness is to model the subjectivity and partiality intrinsic in this process.