Preference queries aim at increasing personalized pertinence of a selection. The most famous ones are the skyline queries based on the concept of dominance introduced by Pareto. Many other dominances have been proposed. In particular, many weaker forms of dominance aim at reducing the size of the answer of the skyline query. In most cases, applying just one dominance is not satisfying as it is hard to conciliate high pertinence, i.e. a strong dominance, and reasonable size of the selection. In this talk, I will present a generic approach allowing the user to decide what dominances are reliable, and what priorities between them should be respected. Based on the concept of dominance list, new operators have been defined in order to progressively rank the dataset or select the top-k, which provides a great flexibility to the user.