  There are two most common paradigms that are used in order to identify
records of preference in a multi-objective settings, one relies on dominance,
like the skyline operator, the other instead, on a utility function defined
over the records' attributes, typically using top-k queries. Although they are
very popular, we have to take in account their main disadvantages, which bring
us to describe three hard requirements: personalization, controllable output
size, and flexibility in preference specification. In fact Skyline queries are
simple to specify but they are not equipped with any means to accommodate user
preferences or to control the cardinality of the result set. Ranking queries
adopt, instead, a specific scoring function to rank tuples, and can easily
control the output size, but it is difficult to specify correctly the weights
of this scoring function in order to give different importance to the
attributes. In this paper we describe three different approaches which try to
satisfy the three hard requirements mentioned above embracing the advantages
either of the Skyline queries or of the ranking queries. These approaches are
namely: Flexible Skyline, ORD-ORU and UTK.
