Name
Abstract | ||
|---|---|---|
ABSTRACT Historically, the main criterion for a successful recommender system was the relevance of the recommended items to the user. In other words, the only objective for the recommendation algorithm was to learn user’s preferences for different items and generate recommendations accordingly. However, real-world recommender systems are well beyond a simple objective and often need to take into account multiple objectives simultaneously. These objectives can be either from the users’ perspective or they could come from other stakeholders such as item providers or any party that could be impacted by the recommendations. Such multi-objective and multi-stakeholder recommenders present unique challenges and these challenges were the focus of the MORS workshop. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3460231.3470936 | RECSYS |
Keywords | DocType | Citations |
multi-objective recommendation, Value-aware recommendation | Conference | 0 |
PageRank | References | Authors |
0.34 | 2 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Himan Abdollahpouri | 1 | 89 | 14.23 |
| Mehdi Elahi | 2 | 408 | 29.41 |
| Masoud Mansoury | 3 | 19 | 6.09 |
| Shaghayegh Sahebi | 4 | 66 | 9.48 |
| Zahra Nazari | 5 | 4 | 2.20 |
| Allison June-Barlow Chaney | 6 | 92 | 4.41 |
| Babak Loni | 7 | 0 | 1.01 |