EDBT 2026 Demo / reviewers in the wild / expert
Quanjie Zhang
dblp:284/4827
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics › clustering
hierarchical clustering |
0.5 | 1 | 2021 | SineStream: Improving the Readability of Streamgraphs by Minimizing Sine Illusion Effects · IEEE Trans. Vis. Comput. Graph. 2021 |
Visualization and visual analytics › time series visualization
streamgraph |
0.5 | 1 | 2021 | SineStream: Improving the Readability of Streamgraphs by Minimizing Sine Illusion Effects · IEEE Trans. Vis. Comput. Graph. 2021 |
Methods — techniques the papers use, named apart from their topics
hierarchical clustering · 0.5gaussian weighting · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | SineStream: Improving the Readability of Streamgraphs by Minimizing Sine Illusion EffectsabstractIn this paper, we propose SineStream, a new variant of streamgraphs that improves their readability by minimizing sine illusion effects. Such effects reflect the tendency of humans to take the orthogonal rather than the vertical distance between two curves as their distance. In SineStream, we connect the readability of streamgraphs with minimizing sine illusions and by doing so provide a perceptual foundation for their design. As the geometry of a streamgraph is controlled by its baseline (the bottom-most curve) and the ordering of the layers, we re-interpret baseline computation and layer ordering algorithms in terms of reducing sine illusion effects. For baseline computation, we improve previous methods by introducing a Gaussian weight to penalize layers with large thickness changes. For layer ordering, three design requirements are proposed and implemented through a hierarchical clustering algorithm. Quantitative experiments and user studies demonstrate that SineStream improves the readability and aesthetics of streamgraphs compared to state-of-the-art methods. Chuan Bu, Quanjie Zhang, Qianwen Wang 0001, Jian Zhang 0070, Michael Sedlmair, Oliver Deussen, Yunhai Wang |
IEEE Trans. Vis. Comput. Graph. | 2 |