Modeling Personalized Retweeting Behaviors for Multi-Stage Cascade Popularity Prediction
Abstract
We consider a large-scale incentive allocation problem where the entire trade-off curve between budget and profit has to be maintained approximately at all time. The application originally comes from assigning coupons to users of the ride-sharing apps, where each user can have a limit on the number of coupons been assigned. We consider a more general form, where the coupons for each user forms a matroid, and the coupon assigned to each user must be an independent set. We show the entire trade-off curve can be maintained approximately in near real time.
Cite
Text
Zhou et al. "Modeling Personalized Retweeting Behaviors for Multi-Stage Cascade Popularity Prediction." International Joint Conference on Artificial Intelligence, 2024. doi:10.24963/ijcai.2024/287Markdown
[Zhou et al. "Modeling Personalized Retweeting Behaviors for Multi-Stage Cascade Popularity Prediction." International Joint Conference on Artificial Intelligence, 2024.](https://mlanthology.org/ijcai/2024/zhou2024ijcai-modeling/) doi:10.24963/ijcai.2024/287BibTeX
@inproceedings{zhou2024ijcai-modeling,
title = {{Modeling Personalized Retweeting Behaviors for Multi-Stage Cascade Popularity Prediction}},
author = {Zhou, Mingyang and Lin, Yanjie and Liu, Gang and Li, Zuwen and Liao, Hao and Mao, Rui},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2024},
pages = {2598-2606},
doi = {10.24963/ijcai.2024/287},
url = {https://mlanthology.org/ijcai/2024/zhou2024ijcai-modeling/}
}