Flexible skyline: overview and applicability

04/30/2022
by   Carlo Bellacoscia, et al.
0

Ranking (or top-k) and skyline queries are the most popular approaches used to extract interesting data from large datasets. The first one is based on a scoring function to evaluate and rank tuples. Its computation is fast, but it is sensitive to the choice of the evaluating function. Skyline queries are based on the idea of dominance and the result is the set of all non-dominated tuples. This is a very interesting approach, but it can't allow to control the cardinality of the output. Recent researches discovered more techniques to compensate for these drawbacks. In particular, this paper will focus on the flexible skyline approach.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/10/2022

A Skyline and ranking query odissey: a journey from skyline and ranking queries up to f-skyline queries

Skyline and ranking queries are two of the most used tools to manage lar...
research
02/25/2022

Getting the best from skylines and top-k queries

Top-k and skylines are two important techniques that can be used to extr...
research
02/21/2022

Flexible Skylines: Customizing Skyline Queries Catching Desired Preferences

The techniques most extensively used to retrieve interesting data from d...
research
02/20/2022

Multi-objective optimization: basic approaches and moving beyond them through flexible skyline queries

The area of scientific research that deals with the simultaneous optimiz...
research
01/25/2022

Poisson's CDF applied to Flexible Skylines

The evolution of skyline and ranking queries has created new archetypes ...
research
01/28/2022

A survey on flexible/restricted skyline and their applicability

Skyline and Top-k are two of the most important methods to extract infor...

Please sign up or login with your details

Forgot password? Click here to reset