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Santhosh Nandhakumar

dblp:232/9018 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0002-7674-6138ORCID · reported

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 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics › visual encoding
glyph-based visualization
0.612022
GridSet: Visualizing Individual Elements and Attributes for Analysis of Set-Typed Data · IEEE Trans. Vis. Comput. Graph. 2022
Visualization and visual analytics
set visualization
0.612022
GridSet: Visualizing Individual Elements and Attributes for Analysis of Set-Typed Data · IEEE Trans. Vis. Comput. Graph. 2022

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

visual links · 0.6set operations · 0.6
YearPublicationVenuePosition
2022 GridSet: Visualizing Individual Elements and Attributes for Analysis of Set-Typed Data
abstract
We present GridSet, a novel set visualization for exploring elements, their attributes, intersections, as well as entire sets. In this set visualization, each set representation is composed of glyphs, which represent individual elements and their attributes utilizing different visual encodings. In each set, elements are organized within a grid treemap layout that can provide space-efficient overviews of the elements structured by set intersections across multiple sets. These intersecting elements can be connected among sets through visual links. These visual representations for the individual set, elements, and intersection in GridSet facilitate novel interaction approaches for undertaking analysis tasks by utilizing both macroscopic views of sets, as well as microscopic views of elements and attribute details. In order to perform multiple set operations, GridSet supports a simple and straightforward process for set operations through dragging and dropping set objects. Our use cases involving two large set-typed datasets demonstrate that GridSet facilitates the exploration and identification of meaningful patterns and distributions of elements with respect to attributes and set intersections for solving complex analysis problems in set-typed data.
Haeyong Chung, Santhosh Nandhakumar, Seungwon Yang
IEEE Trans. Vis. Comput. Graph.2