Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning.

Dusan Stamenkovic|Alexandros Karatzoglou|Ioannis Arapakis|Xin Xin|Kleomenis Katevas


Anthology ID:DBLP:conf/wsdm/StamenkovicKAXK22
Volume:WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022
Year:2022
Venue:Web Search and Data Mining (WSDM)
Publisher:ACM
Pages:957-965
URL:https://doi.org/10.1145/3488560.3498471
DOI:https://doi.org/10.1145/3488560.3498471
DBLP:conf/wsdm/StamenkovicKAXK22
BibTeX:
@inproceedings{stamenkovic-2022-choosing, author = {Dusan Stamenkovic and Alexandros Karatzoglou and Ioannis Arapakis and Xin Xin and Kleomenis Katevas}, editor = {K. Sel\c{c}uk Candan and Huan Liu and Leman Akoglu and Xin Dong and Jiliang Tang}, title = {{Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning}}, booktitle = {{WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022}}, pages = {957--965}, publisher = {ACM}, year = {2022}, url = {https://doi.org/10.1145/3488560.3498471}, doi = {https://doi.org/10.1145/3488560.3498471} }