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

TL;DR

This paper reviews the evolution of skyline and ranking queries, introduces f-skyline queries as an improvement, and compares these methods to highlight advancements and limitations addressed.

Contribution

It provides a comprehensive overview of skyline, ranking, and f-skyline queries, emphasizing their differences and improvements over traditional approaches.

Findings

f-skyline queries overcome some limitations of skyline and ranking queries

comparison shows improved flexibility and result management with f-skyline

the paper highlights how f-skyline addresses previous drawbacks

Abstract

Skyline and ranking queries are two of the most used tools to manage large data sets. The former is based on non-dominance, while the latter on a scoring function. Despite their effectiveness, they have some drawbacks like the result size or the need for a utility function that must be taken into account. To do this, in the last years, new kinds of queries, called flexible skyline queries, have been developed. In the present article, a description of skyline and ranking queries, f-skyline queries and a comparison among them are provided to highlight the improvements achieved and how some limitations have been overcome.