SkyFlow: A visual analysis of high-dimensional skylines in time-series
- Authors
- Kim, Wooil; Shim, Changbeom; Chung, Yon Dohn
- Issue Date
- 10월-2021
- Publisher
- SPRINGER
- Keywords
- Skyline in time-series data; Time-varying multi-criteria decision-making; Visual analytics
- Citation
- JOURNAL OF VISUALIZATION, v.24, no.5, pp.1033 - 1050
- Indexed
- SCIE
SCOPUS
- Journal Title
- JOURNAL OF VISUALIZATION
- Volume
- 24
- Number
- 5
- Start Page
- 1033
- End Page
- 1050
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/136131
- DOI
- 10.1007/s12650-021-00758-y
- ISSN
- 1343-8875
- Abstract
- Decision makers often find themselves in situations where they need to consider time-varying values for multi-criteria decision-making. Skyline queries are one of the most widely used methods of approaching multi-criteria decision-making problems because they reduce the size of search space by excluding inferior data. However, skylines in time-series data fluctuate with changes in attributes. Moreover, the number of skyline points increases as the number of dimensions increases, and the skyline query itself does not provide any ranking method. Thus, users are required to direct a considerable amount of effort into analyzing and finding the best selection. To address these issues, we propose SkyFlow, a visual analytical system for comparing time-varying data to facilitate the decision-making process. We apply two datasets in our system and describe scenarios to demonstrate the effectiveness of SkyFlow. In addition, we conduct a qualitative study to highlight the efficiency of our system in assisting users to compare candidates and make decisions involving time-series data. Graphic abstract
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Collections - Graduate School > Department of Computer Science and Engineering > 1. Journal Articles
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