Flexible Skyline: one query to rule them all

TL;DR

This paper introduces Flexible Skylines, a unified framework that combines top-k and skyline query methods using F-dominance, aiming to leverage the strengths of both approaches for relevant data retrieval.

Contribution

The paper presents a novel framework called Flexible Skylines that integrates ranking and skyline queries through F-dominance, enhancing query flexibility and effectiveness.

Findings

Flexible Skylines unify top-k and skyline queries.

F-dominance enables combining ranking and Pareto-based methods.

The framework improves relevance and flexibility in data retrieval.

Abstract

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.