Hong Wen
Orcid: 0000-0002-6924-2839Affiliations:
- Alibaba Group, Hangzhou, China
According to our database1,
Hong Wen
authored at least 26 papers
between 2018 and 2024.
Collaborative distances:
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Bibliography
2024
Collaboration or Competition: An Infomax-Based Period-Aware Transformer for Ticket-Grabbing Prediction.
IEEE Trans. Intell. Transp. Syst., December, 2024
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024
UID-Net: Enhancing Click-Through Rate Prediction in Trigger-Induced Recommendation Through User Interest Decomposition.
Proceedings of the Advanced Data Mining and Applications - 20th International Conference, 2024
2023
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
MOEF: Modeling Occasion Evolution in Frequency Domain for Promotion-Aware Click-Through Rate Prediction.
Proceedings of the Database Systems for Advanced Applications, 2023
Proceedings of the Database Systems for Advanced Applications, 2023
2022
Deep Interest Highlight Network for Click-Through Rate Prediction in Trigger-Induced Recommendation.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022
MetaCVR: Conversion Rate Prediction via Meta Learning in Small-Scale Recommendation Scenarios.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
A Dual Channel Intent Evolution Network for Predicting Period-Aware Travel Intentions at Fliggy.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
Hierarchically Fusing Long and Short-Term User Interests for Click-Through Rate Prediction in Product Search.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
SMINet: State-Aware Multi-Aspect Interests Representation Network for Cold-Start Users Recommendation.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
Conversion Rate Prediction via Meta Learning in Small-Scale Recommendation Scenarios.
CoRR, 2021
SAME: Scenario Adaptive Mixture-of-Experts for Promotion-Aware Click-Through Rate Prediction.
CoRR, 2021
Hierarchically Modeling Micro and Macro Behaviors via Multi-Task Learning for Conversion Rate Prediction.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021
SAR-Net: A Scenario-Aware Ranking Network for Personalized Fair Recommendation in Hundreds of Travel Scenarios.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021
2020
Large-scale Causal Approaches to Debiasing Post-click Conversion Rate Estimation with Multi-task Learning.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020
Entire Space Multi-Task Modeling via Post-Click Behavior Decomposition for Conversion Rate Prediction.
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020
GMCM: Graph-based Micro-behavior Conversion Model for Post-click Conversion Rate Estimation.
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020
2019
A Causal Perspective to Unbiased Conversion Rate Estimation on Data Missing Not at Random.
CoRR, 2019
Multi-Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
2018