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| Content Provider | ACM Digital Library |
|---|---|
| Author | Volinsky, Chris Hu, Yifan Gansner, Emden Kobourov, Stephen |
| Abstract | For users, recommendations can sometimes seem odd or counterintuitive. Visualizing recommendations can remove some of this mystery, showing how a recommendation is grouped with other choices. A drawing can also lead a user's eye to other options. Traditional 2D-embeddings of points can be used to create a basic layout, but these methods, by themselves, do not illustrate clusters and neighborhoods very well. In this paper, we propose the use of geographic maps to enhance the definition of clusters and neighborhoods, and consider the effectiveness of this approach in visualizing similarities and recommendations arising from TV shows. |
| Starting Page | 345 |
| Ending Page | 348 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781605584355 |
| DOI | 10.1145/1639714.1639784 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2009-10-23 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Visualization Graph Clustering Recommender system |
| Content Type | Text |
| Resource Type | Article |
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