er may impose privacy constraints on some elements of his profile. In the latter case, the user may require to know which data a system knows about him. A user can have several profiles, depending on his various domains of interest. These profiles act as ubiquitous objects that facilitate users' access to massive data and optimize providers' selection of target customers. Personalization Paradigm in Service Delivery Platforms The user profile definition varies from one application to another, depending on how application designers perceive personalization, regardless of how users want personalization. As a first example, the CASPER project [14] defines a user profile as a sample of searched documents associated with their relevance with respect to user preferences. Another example [18] defines a profile using a set of utility func- tions over a domain of interest: two complementary clauses, DOMAIN and UTILITY, enable to define, respectively, the domain of interest of the user as a set of abstract subjects and the relative importance of these subjects as a set of equa- tions. In [33], the user profile is defined with respect to a database schema as a list of weighted predicates that represent the most frequent selection predicates that are supposed to appear in user queries. Each predicate weight, defined between 0 and 1, emphasizes its relative importance with respect to others. To go beyond these specific definitions, we consider a profile as a mutidimen- sional structure, each dimension being characterized by a set of attributes, possibly organized into abstract entities, whose values can be user defined or dynamically derived from users' behavior. These attributes are generally ranked and organized as sets of preferences that will serve to drive query compilation, query execution, and data delivery. Preference expressions may be of several kinds: introducing partial or total orders within profile predicates or keywords, emphasizing on some attributes or predicates by assigning relative weights, imposing the su