Flexible skylines, regret minimization and skyline ranking: a comparison to know how to select the right approach

01/25/2022
by   Vittorio Fabris, et al.
0

Recent studies pointed out some limitations about classic top-k queries and skyline queries. Ranking queries impose the user to provide a specific scoring function, which can lead to the exclusion of interesting results because of the inaccurate estimation of the assigned weights. The skyline approach makes it difficult to always retrieve an accurate result, in particular when the user has to deal with a dataset whose tuples are defined by semantically different attributes. Therefore, to improve the quality of the final solutions, new techniques have been developed and proposed: here we will discuss about the flexible skyline, regret minimization and skyline ranking approaches. We present a comparison between the three different operators, recalling their way of behaving and defining a guideline for the readers so that it is easier for them to decide which one, among these three, is the best technique to apply to solve their problem.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/22/2022

Comparing the latest ranking techniques: pros and cons of flexible skylines, regret minimization and skyline ranking queries

Long-established ranking approaches, such as top-k and skyline queries, ...
research
02/13/2022

Giving the Right Answer: a Brief Overview on How to Extend Ranking and Skyline Queries

To retrieve the best results in a database we use Top-K queries and Skyl...
research
01/11/2022

Flexible Skyline: one query to rule them all

The most common archetypes to identify relevant information in large dat...
research
11/13/2017

Overlaying Quantitative Measurement on Networks: An Evaluation of Three Positioning and Nine Visual Marker Techniques

We report results from an experiment on ranking visual markers and node ...
research
03/22/2021

Efficient Processing of k-regret Minimization Queries with Theoretical Guarantees

Assisting end users to identify desired results from a large dataset is ...
research
06/06/2022

Comparing modern techniques for querying data starting from top-k and skyline queries

To make intelligent decisions over complex data by discovering a set of ...
research
04/26/2022

Skyline Operators and Regret Minimization Techniques for Managing User Preferences in the Query Process

The problem of selecting the most representative tuples from a dataset h...

Please sign up or login with your details

Forgot password? Click here to reset