Abstract
Group Recommendation Systems (GRS's) assist groups when trying to reach a joint decision. I use probabilistic data and apply voting theory to GRS's in order to minimize user interaction and output an approximate or definite “winner item”.
| Original language | English |
|---|---|
| Pages | 2400-2401 |
| Number of pages | 2 |
| DOIs | |
| State | Published - 2012 |
| Externally published | Yes |
| Event | 26th AAAI Conference on Artificial Intelligence, AAAI 2012 - Toronto, Canada Duration: 22 Jul 2012 → 26 Jul 2012 |
Conference
| Conference | 26th AAAI Conference on Artificial Intelligence, AAAI 2012 |
|---|---|
| Country/Territory | Canada |
| City | Toronto |
| Period | 22/07/12 → 26/07/12 |
Fingerprint
Dive into the research topics of 'Iterative Voting under Uncertainty for Group Recommender Systems (Research Abstract)'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver