Demo Data from EDBT 2026 / reviewers in the wild / expert
Jiepeng Fan
dblp:202/8500
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1
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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics › geospatial visualization
cartographic visualization |
0.3 | 1 | 2017 | Generating Multi-Destination Maps · IEEE Trans. Vis. Comput. Graph. 2017 |
Visualization and visual analytics › graph visualization › graph drawing
constrained graph layout |
0.3 | 1 | 2017 | Generating Multi-Destination Maps · IEEE Trans. Vis. Comput. Graph. 2017 |
Visualization and visual analytics › graph visualization
graph drawing |
0.3 | 1 | 2017 | Generating Multi-Destination Maps · IEEE Trans. Vis. Comput. Graph. 2017 |
Methods — techniques the papers use, named apart from their topics
perturbation-based optimization · 0.3graph drawing · 0.3constrained optimization · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Generating Multi-Destination MapsabstractMulti-destination maps are a kind of navigation maps aimed to guide visitors to multiple destinations within a region, which can be of great help to urban visitors. However, they have not been developed in the current online map service. To address this issue, we introduce a novel layout model designed especially for generating multi-destination maps, which considers the global and local layout of a multi-destination map. We model the layout problem as a graph drawing that satisfies a set of hard and soft constraints. In the global layout phase, we balance the scale factor between ROIs. In the local layout phase, we make all edges have good visibility and optimize the map layout to preserve the relative length and angle of roads. We also propose a perturbation-based optimization method to find an optimal layout in the complex solution space. The multi-destination maps generated by our system are potential feasible on the modern mobile devices and our result can show an overview and a detail view of the whole map at the same time. In addition, we perform a user study to evaluate the effectiveness of our method, and the results prove that the multi-destination maps achieve our goals well. Junsong Zhang, Jiepeng Fan, Zhenshan Luo |
IEEE Trans. Vis. Comput. Graph. | 2 |