Multi-level interaction reranking with user behavior history

Y **, W Liu, J Zhu, X Zhao, X Dai, R Tang… - Proceedings of the 45th …, 2022 - dl.acm.org
As the final stage of the multi-stage recommender system (MRS), reranking directly affects
users' experience and satisfaction, thus playing a critical role in MRS. Despite the …

Utility-Oriented Reranking with Counterfactual Context

Y **, W Liu, X Dai, R Tang, Q Liu, W Zhang… - ACM Transactions on …, 2024 - dl.acm.org
As a critical task for large-scale commercial recommender systems, reranking rearranges
items in the initial ranking lists from the previous ranking stage to better meet users' …

Personalized diversification for neural re-ranking in recommendation

W Liu, Y **, J Qin, X Dai, R Tang, S Li… - 2023 IEEE 39th …, 2023 - ieeexplore.ieee.org
Re-ranking, as the final stage of the multi-stage recommender systems (MRS), aims at
modeling the listwise context and the cross-item interactions between the candidate items …

Tdcm: Transport destination calibrating based on multi-task learning

T Wu, K Zhu, J Mao, M Yang, A Zhou - Joint European Conference on …, 2023 - Springer
Accurate location and address of destination are critical for bulk commodity transportation,
which determines the service quality of the logistics applications such as transport task …

Topological Knowledge Enhanced Personalized Ranking Model for Sequential Medication Recommendation

Y Wang, L Yue, Y Li - International Conference on Advanced Data Mining …, 2024 - Springer
Sequential medication recommendation is a crucial healthcare application designed to
administer medications in appropriate sequences. While clinical records offer extensive …