RGRecSys: A Toolkit for Robustness Evaluation of Recommender Systems.
Zohreh Ovaisi|Shelby Heinecke|Jia Li|Yongfeng Zhang|Elena Zheleva|Caiming Xiong
| Anthology ID: | DBLP:conf/wsdm/OvaisiHLZZX22 |
|---|---|
| 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: | 1597-1600 |
| URL: | https://doi.org/10.1145/3488560.3502192 |
| DOI: | https://doi.org/10.1145/3488560.3502192 |
| DBLP: | conf/wsdm/OvaisiHLZZX22 |
| BibTeX: |
@inproceedings{ovaisi-2022-rgrecsys,
author = {Zohreh Ovaisi and
Shelby Heinecke and
Jia Li and
Yongfeng Zhang and
Elena Zheleva and
Caiming Xiong},
editor = {K. Sel\c{c}uk Candan and
Huan Liu and
Leman Akoglu and
Xin Dong and
Jiliang Tang},
title = {{RGRecSys: A Toolkit for Robustness Evaluation of Recommender Systems}},
booktitle = {{WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022}},
pages = {1597--1600},
publisher = {ACM},
year = {2022},
url = {https://doi.org/10.1145/3488560.3502192},
doi = {https://doi.org/10.1145/3488560.3502192}
}