Generating Euler Diagrams Through Combinatorial Optimization
| dc.contributor.author | Rottmann, Peter | en_US |
| dc.contributor.author | Rodgers, Peter | en_US |
| dc.contributor.author | Yan, Xinyuan | en_US |
| dc.contributor.author | Archambault, Daniel | en_US |
| dc.contributor.author | Wang, Bei | en_US |
| dc.contributor.author | Haunert, Jan-Henrik | en_US |
| dc.contributor.editor | Aigner, Wolfgang | en_US |
| dc.contributor.editor | Archambault, Daniel | en_US |
| dc.contributor.editor | Bujack, Roxana | en_US |
| dc.date.accessioned | 2024-05-21T08:18:17Z | |
| dc.date.available | 2024-05-21T08:18:17Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | Can a given set system be drawn as an Euler diagram? We present the first method that correctly decides this question for arbitrary set systems if the Euler diagram is required to represent each set with a single connected region. If the answer is yes, our method constructs an Euler diagram. If the answer is no, our method yields an Euler diagram for a simplified version of the set system, where a minimum number of set elements have been removed. Further, we integrate known wellformedness criteria for Euler diagrams as additional optimization objectives into our method. Our focus lies on the computation of a planar graph that is embedded in the plane to serve as the dual graph of the Euler diagram. Since even a basic version of this problem is known to be NP-hard, we choose an approach based on integer linear programming (ILP), which allows us to compute optimal solutions with existing mathematical solvers. For this, we draw upon previous research on computing planar supports of hypergraphs and adapt existing ILP building blocks for contiguity-constrained spatial unit allocation and the maximum planar subgraph problem. To generate Euler diagrams for large set systems, for which the proposed simplification through element removal becomes indispensable, we also present an efficient heuristic. We report on experiments with data from MovieDB and Twitter. Over all examples, including 850 non-trivial instances, our exact optimization method failed only for one set system to find a solution without removing a set element. However, with the removal of only a few set elements, the Euler diagrams can be substantially improved with respect to our wellformedness criteria. | en_US |
| dc.description.number | 3 | |
| dc.description.sectionheaders | Geospatial Data and Optimization | |
| dc.description.seriesinformation | Computer Graphics Forum | |
| dc.description.volume | 43 | |
| dc.identifier.doi | 10.1111/cgf.15089 | |
| dc.identifier.issn | 1467-8659 | |
| dc.identifier.pages | 12 pages | |
| dc.identifier.uri | https://doi.org/10.1111/cgf.15089 | |
| dc.identifier.uri | https://diglib.eg.org/handle/10.1111/cgf15089 | |
| dc.publisher | The Eurographics Association and John Wiley & Sons Ltd. | en_US |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | |
| dc.subject | CCS Concepts: Human-centered computing → Information visualization; Theory of computation → Integer programming; Mathematics of computing → Hypergraphs | |
| dc.subject | Human centered computing → Information visualization | |
| dc.subject | Theory of computation → Integer programming | |
| dc.subject | Mathematics of computing → Hypergraphs | |
| dc.title | Generating Euler Diagrams Through Combinatorial Optimization | en_US |