  The most common archetypes to identify relevant information in large datasets
and find the bestoptions according to some preferences or user criteria, are
the top-k queries (ranking method based ona score function defined over the
records attributes) and skyline queries (based on Pareto dominance oftuples).
Despite their large diffusion, both approaches have their pros and cons. In
this survey paper, a comparison is made between these methods and the Flexible
Skylines, which is a framework that combines the ranking and skyline approaches
using the novel concept ofF-dominanceto a set of monotone scoring function F.
