| dc.contributor.author |
Hu, C |
|
| dc.coverage.spatial |
Technology Engagement Center, Duke University |
|
| dc.date.accessioned |
2017-02-28T18:32:10Z |
|
| dc.date.available |
2017-02-28T18:32:10Z |
|
| dc.date.issued |
2017-02-28 |
|
| dc.identifier.uri |
https://hdl.handle.net/10161/13697 |
|
| dc.description.abstract |
The goal of this visualization was to examine the geographic spread of collaborations
represented in the scholars@duke dataset. The goal of the Scholars@Duke Visualization
Challenge was to create visualizations that capture the richness and dynamism of Duke
research. The datasets were provided by Scholars@Duke (https://schoalrs.duke.edu/)
and they describe publications, authorships, and scholarly collaborations from university
researchers over the past 5 years.
|
|
| dc.publisher |
Duke Research Computing |
|
| dc.source |
Scholars@Duke Data Visualization Challenge |
|
| dc.title |
Analyzing Scholars@Duke Data via Tensor Factorization |
|
| dc.type |
Conference |
|
| duke.contributor.id |
Hu, C|0581276 |
|
| pubs.finish-date |
2017-01-20 |
|
| pubs.organisational-group |
Duke |
|
| pubs.organisational-group |
Student |
|
| pubs.publisher-url |
https://rc.duke.edu/scholars-vis-challenge/ |
|
| pubs.start-date |
2017-01-18 |
|
