MODRL-TA: A Multi-Objective Deep Reinforcement Learning Framework for Traffic Allocation in E-Commerce Search.

Peng Cheng|Huimu Wang|Jinyuan Zhao|Yihao Wang|Enqiang Xu|Yu Zhao|Zhuojian Xiao|Songlin Wang|Guoyu Tang|Lin Liu|Sulong Xu


Anthology ID:DBLP:conf/cikm/ChengWZWXZXWTLX24
Volume:Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024
Year:2024
Venue:International Conference on Information and Knowledge Management (CIKM)
Publisher:ACM
Pages:3694-3698
URL:https://doi.org/10.1145/3627673.3679964
DOI:https://doi.org/10.1145/3627673.3679964
DBLP:conf/cikm/ChengWZWXZXWTLX24
BibTeX:
@inproceedings{cheng-2024-modrlta, author = {Peng Cheng and Huimu Wang and Jinyuan Zhao and Yihao Wang and Enqiang Xu and Yu Zhao and Zhuojian Xiao and Songlin Wang and Guoyu Tang and Lin Liu and Sulong Xu}, editor = {Edoardo Serra and Francesca Spezzano}, title = {{MODRL-TA: A Multi-Objective Deep Reinforcement Learning Framework for Traffic Allocation in E-Commerce Search}}, booktitle = {{Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024}}, pages = {3694--3698}, publisher = {ACM}, year = {2024}, url = {https://doi.org/10.1145/3627673.3679964}, doi = {https://doi.org/10.1145/3627673.3679964} }