Counting stars: a survey on flexible Skyline Query approaches

TL;DR

This survey reviews recent flexible skyline query methods developed in the last decade, comparing their performance to traditional top-k and skyline queries to aid data filtering and ranking.

Contribution

It provides a comprehensive overview of recent skyline query approaches, highlighting their applications and performance improvements over traditional methods.

Findings

Recent skyline approaches offer flexible data filtering options.

Flexible skyline methods outperform traditional skyline queries in certain scenarios.

The survey identifies key trends and future directions in skyline query research.

Abstract

Nowadays, as the quantity of data to process began to rise, so did the need for a method to discern what pieces of information could be useful for the user; in response, researchers focused their efforts on improving the already existing ranking methods or creating new ones starting from them. This survey will be presented a small list of some of the most known and/or most recent solutions proposed, with some possible applications for them, concerning a state of the art restricted to around the last ten years, comparing their performance with the traditional one top-k and skyline queries.