Name
Abstract | ||
|---|---|---|
Labeling data instances is an important task in machine learning and visual analytics. Both fields provide a broad set of labeling strategies, whereby machine learning (and in particular active learning) follows a rather model-centered approach and visual analytics employs rather user-centered approaches (visual-interactive labeling). Both approaches have individual strengths and weaknesses. In th... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TVCG.2017.2744818 | IEEE Transactions on Visualization and Computer Graphics |
Keywords | Field | DocType |
Labeling,Visual analytics,Data models,Uncertainty,Data visualization | Data modeling,Data visualization,Dimensionality reduction,Active learning,Information visualization,Computer science,Visual analytics,Theoretical computer science,Artificial intelligence,Strengths and weaknesses,Machine learning | Journal |
Volume | Issue | ISSN |
24 | 1 | 1077-2626 |
Citations | PageRank | References |
21 | 0.66 | 37 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jürgen Bernard | 1 | 334 | 32.32 |
| Marco Hutter | 2 | 460 | 58.00 |
| Matthias Zeppelzauer | 3 | 186 | 21.35 |
| Dieter Fellner | 4 | 173 | 12.32 |
| Michael Sedlmair | 5 | 915 | 51.74 |