  A set of preferred records can be obtained from a large database in a
multi-criteria setting using various computational methods which either depend
on the concept of dominance or on the concept of utility or scoring function
based on the attributes of the database record. A skyline approach relies on
the dominance relationship between different data points to discover
interesting data from a huge database. On the other hand, ranking queries make
use of specific scoring functions to rank tuples in a database. An experimental
evaluation of datasets can provides us with information on the effectiveness of
each of these methods.
