Visualizing Time-Dependent Data Using Dynamic t-SNE
| dc.contributor.author | Rauber, Paulo E. | en_US |
| dc.contributor.author | Falcão, Alexandre X. | en_US |
| dc.contributor.author | Telea, Alexandru C. | en_US |
| dc.contributor.editor | Enrico Bertini and Niklas Elmqvist and Thomas Wischgoll | en_US |
| dc.date.accessioned | 2016-06-09T09:42:26Z | |
| dc.date.available | 2016-06-09T09:42:26Z | |
| dc.date.issued | 2016 | en_US |
| dc.description.abstract | Many interesting processes can be represented as time-dependent datasets. We define a time-dependent dataset as a sequence of datasets captured at particular time steps. In such a sequence, each dataset is composed of observations (high-dimensional real vectors), and each observation has a corresponding observation across time steps. Dimensionality reduction provides a scalable alternative to create visualizations (projections) that enable insight into the structure of such datasets. However, applying dimensionality reduction independently for each dataset in a sequence may introduce unnecessary variability in the resulting sequence of projections, which makes tracking the evolution of the data significantly more challenging. We show that this issue affects t-SNE, a widely used dimensionality reduction technique. In this context, we propose dynamic t-SNE, an adaptation of t-SNE that introduces a controllable trade-off between temporal coherence and projection reliability. Our evaluation in two time-dependent datasets shows that dynamic t-SNE eliminates unnecessary temporal variability and encourages smooth changes between projections. | en_US |
| dc.description.sectionheaders | Multidimensional and Geospatial Visualization | en_US |
| dc.description.seriesinformation | EuroVis 2016 - Short Papers | en_US |
| dc.identifier.doi | 10.2312/eurovisshort.20161164 | en_US |
| dc.identifier.isbn | 978-3-03868-014-7 | en_US |
| dc.identifier.issn | - | en_US |
| dc.identifier.pages | 73-77 | en_US |
| dc.identifier.uri | https://doi.org/10.2312/eurovisshort.20161164 | en_US |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10 | |
| dc.publisher | The Eurographics Association | en_US |
| dc.subject | Human | en_US |
| dc.subject | centered computing | en_US |
| dc.subject | Information visualization | en_US |
| dc.subject | Computing methodologies | en_US |
| dc.subject | Dimensionality reduction and manifold learning | en_US |
| dc.title | Visualizing Time-Dependent Data Using Dynamic t-SNE | en_US |