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Tim van Gelder

dblp:23/5522 · also Timothy van Gelder · DBLP profile ↗
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2ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0001-5606-495XORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1Applied, interdisciplinary, general and emerging computing · 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%
Theoretical computer science
1 paper
Computational geometry · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics
hierarchical data visualization
0.112011
Hi-Trees and Their Layout · IEEE Trans. Vis. Comput. Graph. 2011
Computational geometry › graph drawing
tree drawing
0.012011
Hi-Trees and Their Layout · IEEE Trans. Vis. Comput. Graph. 2011

Methods — techniques the papers use, named apart from their topics

bottom-up tree layout algorithm · 0.2
YearPublicationVenuePosition
2022 Measuring Quality of General Reasoning
Alexandru Marcoci, Tim van Gelder, Simon Dennis 0001, Margaret Webb, Luke Rowe, Ashley Barnett, Tamar Primoratz, Ariel Kruger, Benjamin Stone, Michael L. Diamond, Morgan Saletta
CogSci2
2011 Hi-Trees and Their Layout
abstract
We introduce hi-trees, a new visual representation for hierarchical data in which, depending on the kind of parent node, the child relationship is represented using either containment or links. We give a drawing convention for hi-trees based on the standard layered drawing convention for rooted trees, then show how to extend standard bottom-up tree layout algorithms to draw hi-trees in this convention. We also explore a number of other more compact layout styles for layout of larger hi-trees and give algorithms for computing these. Finally, we describe two applications of hi-trees: argument mapping and business decision support.
Kim Marriott, Peter Sbarski, Tim van Gelder, Daniel Prager, Andy Bulka
IEEE Trans. Vis. Comput. Graph.3