Publication Type

Journal Article

Version

acceptedVersion

Publication Date

1-2018

Abstract

Skyline queries have wide-ranging applications in fields that involve multi-criteria decision making, including tourism, retail industry, and human resources. By automatically removing incompetent candidates, skyline queries allow users to focus on a subset of superior data items (i.e.. the skyline), thus reducing the decision-making overhead. However, users are still required to interpret and compare these superior items manually before making a successful choice. This task is challenging because of two issues. First, people usually have fuzzy, unstable, and inconsistent preferences when presented with multiple candidates. Second, skyline queries do not reveal the reasons for the superiority of certain skyline points in a multi-dimensional space. To address these issues, we propose SkyLens, a visual analytic system aiming at revealing the superiority of skyline points from different perspectives and at different scales to aid users in their decision making. Two scenarios demonstrate the usefulness of SkyLens on two datasets with a dozen of attributes. A qualitative study is also conducted to show that users can efficiently accomplish skyline understanding and comparison tasks with SkyLens.

Keywords

Skyline query, skyline visualization, multi-dimensional data, visual analytics, multi-criteria decision making

Discipline

Databases and Information Systems | Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

IEEE Transactions on Visualization and Computer Graphics

Volume

24

Issue

1

First Page

246

Last Page

255

ISSN

1077-2626

Identifier

10.1109/TVCG.2017.2744738

Publisher

Institute of Electrical and Electronics Engineers

Additional URL

https://doi.org/10.1109/TVCG.2017.2744738

Download

Share

COinS