Classement d'objets Skylines dans les bases de donn{\'e}es
Abstract
Multi-criteria decision analysis in databases has been actively studied, especially through the Skyline operator. Yet, few approaches offer a relevant comparison of Pareto optimal, or Skyline, points for high cardinality result sets. We propose to improve the dp-idp method, inspired by tf-idf, a recent approach computing a score for each Skyline point, by introducing the concept of dominance hierarchy. As dp-idp does not ensure a distinctive rank, we introduce the TOPSIS based CoSky method, derived from both information research and multi-criteria analysis. CoSky, directly embeddable in DBMS, automatically ponderates normalized attributes using the Gini index, then computes a score using Salton's cosine toward an ideal point. By coupling multilevel Skyline to CoSky, we introduce DeepSky. CoSky and dp-idp implementations are evaluated experimentally.
Cite
@article{arxiv.2411.02013,
title = {Classement d'objets Skylines dans les bases de donn{\'e}es},
author = {Mickaël Martin-Nevot and Lotfi Lakhal},
journal= {arXiv preprint arXiv:2411.02013},
year = {2024}
}
Comments
in French language