Name
Abstract | ||
|---|---|---|
Visual analytics systems combine machine learning or other analytic techniques with interactive data visualization to promote sensemaking and analytical reasoning. It is through such techniques that people can make sense of large, complex data. While progress has been made, the tactful combination of machine learning and data visualization is still under-explored. This state-of-the-art report presents a summary of the progress that has been made by highlighting and synthesizing select research advances. Further, it presents opportunities and challenges to enhance the synergy between machine learning and visual analytics for impactful future research directions. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1111/cgf.13092 | COMPUTER GRAPHICS FORUM |
Keywords | DocType | Volume |
visual analytics,information visualization,data mining | Journal | 36.0 |
Issue | ISSN | Citations |
8.0 | 0167-7055 | 33 |
PageRank | References | Authors |
0.81 | 113 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alex Endert | 1 | 974 | 52.18 |
| William Ribarsky | 2 | 2057 | 157.91 |
| Cagatay Turkay | 3 | 287 | 22.63 |
| B. L. William Wong | 4 | 274 | 45.09 |
| Ian T. Nabney | 5 | 119 | 20.10 |
| Ignacio Díaz Blanco | 6 | 81 | 10.36 |
| fabrice rossi | 7 | 603 | 53.90 |