The Challenge of Branch-Aware Data Manifold Exploration

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Date
2023
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Branches within clusters can represent meaningful subgroups that should be explored. In general, automatically detecting branching structures within clusters requires analysing the distances between data points and a centrality metric, resulting in a complex two-dimensional hierarchy. This poster describes abstractions for this data and formulates requirements for a visualisation, building towards a comprehensive branch-aware cluster exploration interface.
Description

CCS Concepts: Computing methodologies -> Cluster analysis; Dimensionality reduction and manifold learning

        
@inproceedings{
10.2312:evp.20231071
, booktitle = {
EuroVis 2023 - Posters
}, editor = {
Gillmann, Christina
and
Krone, Michael
and
Lenti, Simone
}, title = {{
The Challenge of Branch-Aware Data Manifold Exploration
}}, author = {
Bot, Daniƫl M.
and
Peeters, Jannes
and
Aerts, Jan
}, year = {
2023
}, publisher = {
The Eurographics Association
}, ISBN = {
978-3-03868-220-2
}, DOI = {
10.2312/evp.20231071
} }
Citation