Choosing from skyline sets
K. Touloumis (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Christoph Lofi – Mentor (TU Delft - Web Information Systems)
G.J.P.M. Houben – Coach (TU Delft - Web Information Systems)
Casper Bach Bach Poulsen – Graduation committee member (TU Delft - Programming Languages)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
The skyline operator has been proposed to bridge the gap between traditional and multimedia database systems by finding the optimal objects according to the notion of Pareto dominance. According to the notion of Pareto dominance an object dominates another if it is better in one attribute and equal in all others. Skyline sets end up being pretty large because of the "curse of dimensionality". Many skyline reduction algorithms have been proposed to choose "interesting" objects from skyline sets in order to reduce their size. The purpose of this master thesis is to propose a new way of using reduction algorithms, that is to summarize datasets. A framework is proposed for interactive query refinement that will give users an overview of their query results provided by a skyline reduction algorithm. On the grounds of summarizing datasets different reduction algorithms will be compared against each other and a new novel reduction algorithm will be proposed that will hopefully summarize better query results.