Poisson's CDF applied to Flexible Skylines

TL;DR

This paper explores using the Poisson distribution as a scoring function in flexible skyline queries, proposing a method to express user requirements and analyzing algorithmic applications for multi-objective data selection.

Contribution

It introduces a novel application of the Poisson distribution in flexible skyline processes and proposes a new way to model user requirements with F-dominant sets.

Findings

Poisson-based scoring improves skyline relevance

Method for expressing user preferences via F[1] variations

Potential applications in multi-objective optimization

Abstract

The evolution of skyline and ranking queries has created new archetypes like flexible skylines, which have proven to be an efficient method to select relevant data from large datasets using multi objective optimization. This paper aims to study the possible applications of Poisson distribution mass function as a monotonic scoring function in flexible skyline processes, especially those featuring schemas whose attributes can be translated to constant mean rates. Moreover, a method to express users's requirement by means of the F-dominant set of tuples will be proposed using parametrical variations in F[1], simultaneously, algorithm construction and potential applications will be studied.