A Counterfactual Modeling Framework for Churn Prediction.
Guozhen Zhang|Jinwei Zeng|Zhengyue Zhao|Depeng Jin|Yong Li
| Anthology ID: | DBLP:conf/wsdm/ZhangZZJL22 |
|---|---|
| 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: | 1424-1432 |
| URL: | https://doi.org/10.1145/3488560.3498468 |
| DOI: | https://doi.org/10.1145/3488560.3498468 |
| DBLP: | conf/wsdm/ZhangZZJL22 |
| BibTeX: |
@inproceedings{zhang-2022-counterfactual,
author = {Guozhen Zhang and
Jinwei Zeng and
Zhengyue Zhao and
Depeng Jin and
Yong Li},
editor = {K. Sel\c{c}uk Candan and
Huan Liu and
Leman Akoglu and
Xin Dong and
Jiliang Tang},
title = {{A Counterfactual Modeling Framework for Churn Prediction}},
booktitle = {{WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022}},
pages = {1424--1432},
publisher = {ACM},
year = {2022},
url = {https://doi.org/10.1145/3488560.3498468},
doi = {https://doi.org/10.1145/3488560.3498468}
}