Multi-Criteria Optimization for Automatic Dashboard Design
| dc.contributor.author | Choi, Jiwon | en_US |
| dc.contributor.author | Jo, Jaemin | en_US |
| dc.contributor.editor | Gillmann, Christina | en_US |
| dc.contributor.editor | Krone, Michael | en_US |
| dc.contributor.editor | Lenti, Simone | en_US |
| dc.date.accessioned | 2023-06-10T06:31:33Z | |
| dc.date.available | 2023-06-10T06:31:33Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | We present Gleaner, an automatic dashboard design system that optimizes the design in terms of four design criteria, namely Specificity, Interestingness, Diversity, and Coverage. With these criteria, Gleaner not only optimizes for the expressiveness and interestingness of a single visualization but also improves the diversity and coverage of the dashboard as a whole. Users are able to express their intent for desired dashboard design to Gleaner, including specifying preferred or constrained attributes and adjusting the weight of each criterion. This flexibility in expressing intent enables Gleaner to design dashboards that are well-aligned with the user's own analytic goals leading to more efficient data exploration. | en_US |
| dc.description.seriesinformation | EuroVis 2023 - Posters | |
| dc.identifier.doi | 10.2312/evp.20231064 | |
| dc.identifier.isbn | 978-3-03868-220-2 | |
| dc.identifier.pages | 45-47 | |
| dc.identifier.pages | 3 pages | |
| dc.identifier.uri | https://doi.org/10.2312/evp.20231064 | |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/evp20231064 | |
| dc.publisher | The Eurographics Association | en_US |
| dc.rights | Attribution 4.0 International License | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.title | Multi-Criteria Optimization for Automatic Dashboard Design | en_US |