Name
Abstract | ||
|---|---|---|
ABSTRACT The REVEAL workshop1 focuses on framing the recommendation problem as a one of making personalized interventions, e.g. deciding to recommend a particular item to a particular user. Moreover, these interventions sometimes depend on each other, where a stream of interactions occurs between the user and the system, and where each decision to recommend something will have an impact on future steps and long-term rewards. This framing creates a number of challenges we will discuss at the workshop. How can recommender systems be evaluated offline in such a context? How can we learn recommendation policies that are aware of these delayed consequences and outcomes? |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1145/3383313.3411536 | RECSYS |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thorsten Joachims | 1 | 17387 | 1254.06 |
| Yves Raimond | 2 | 373 | 45.93 |
| Olivier Koch | 3 | 0 | 1.01 |
| Maria Dimakopoulou | 4 | 10 | 3.61 |
| Flavian Vasile | 5 | 148 | 13.96 |
| Adith Swaminathan | 6 | 229 | 12.68 |