Comparison of 6 different approaches to outclass Top-k queries and Skyline queries

TL;DR

This survey compares six innovative methods designed to enhance Top-k and Skyline queries, addressing their limitations through various techniques and providing guidance on selecting the most suitable approach.

Contribution

It introduces and compares six recent approaches to improve Top-k and Skyline queries, offering insights into their advantages, disadvantages, and experimental performance.

Findings

Different approaches have unique strengths and weaknesses.

Experimental data helps compare the effectiveness of each method.

Guidance provided for selecting the best approach based on needs.

Abstract

Topk queries and skyline queries have well explored limitations which recent research have tried to complete through new techniques. In this survey, after resuming such limitations, we consider Restricted Skyline Queries, ORD and ORU approach, Krepresentative minimization queries, Skyline ordering queries, UTK queries approach and Skyrank that aim to overcome them. After introducing and comparing their main concepts, pros and cons, we briefly report the algorithms and confront some of the experimental data collected from the bibliography. To conclude the paper, we summarize the results presented with a short guide on how to select the best approach according to specific needs.