Paper Info
Title
Visual Clutter Reduction through Hierarchy-based Projection of High-dimensional Labeled Data.
Abstract
Visualizing high-dimensional labeled data on a two-dimensional plane can quickly result in visual clutter and information overload. To address this problem, the data usually needs to be structured, so that only parts of it are displayed at a time. We present a hierarchy-based approach that projects labeled data on different levels of detail on a two-dimensional plane, whilst keeping the useru0027s cognitive load between the level changes as low as possible. The approach consists of three steps: First, the data is hierarchically clustered; second, the user can determine levels of detail; third, the levels of detail are visualized one at a time on a two-dimensional plane. Animations make transitions between the levels of detail traceable, while the exploration on each level is supported by several interaction techniques. We demonstrate the applicability and usefulness of the approach with use cases from the patent domain and a question-and-answer website.
Year
Venue
Field
2016
Graphics Interface
Visual clutter,Computer vision,Information overload,Use case,Computer science,Artificial intelligence,Labeled data,Hierarchy,Cognitive load
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Dominik Herr1153.60
Qi Han2114.90
Steffen Lohmann362965.25
Thomas Ertl44417401.52