Hierarchically Constrained Adaptive Ad Exposure in Feeds

Author:

Chen Dagui1,Yan Qi1,Chen Chunjie1,Zheng Zhenzhe2,Liu Yangsu2,Ma Zhenjia1,Yu Chuan1,Xu Jian1,Zheng Bo1

Affiliation:

1. Alibaba Group, Beijing, China

2. Shanghai Jiao Tong University, Shanghai, China

Funder

Science and Technology Innovation 2030 ''New Generation Artificial Intelligence" Major Project

China NSF grant

Shanghai Science and Technology fund

Publisher

ACM

Reference28 articles.

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Deep Automated Mechanism Design for Integrating Ad Auction and Allocation in Feed;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10

2. Ad vs Organic: Revisiting Incentive Compatible Mechanism Design in E-commerce Platforms;Proceedings of the ACM Web Conference 2024;2024-05-13

3. Optimally integrating ad auction into e-commerce platforms;Theoretical Computer Science;2023-10

4. PIER: Permutation-Level Interest-Based End-to-End Re-ranking Framework in E-commerce;Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2023-08-04

5. LOVF: Layered Organic View Fusion for Click-through Rate Prediction in Online Advertising;Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval;2023-07-18

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