3 papers
cs.IR2024
Optimizing E-commerce Search: Toward a Generalizable and Rank-Consistent Pre-Ranking Model
Enqiang Xu, Yiming Qiu, Junyang Bai +6
In large e-commerce platforms, search systems are typically composed of a series of modules, including recall, pre-ranking, and ranking phases. The pre-ranking phase, serving as a…
cs.IR2024
Advancing Re-Ranking with Multimodal Fusion and Target-Oriented Auxiliary Tasks in E-Commerce Search
Enqiang Xu, Xinhui Li, Zhigong Zhou +6
In the rapidly evolving field of e-commerce, the effectiveness of search re-ranking models is crucial for enhancing user experience and driving conversion rates. Despite significan…
cs.LG2024
MODRL-TA:A Multi-Objective Deep Reinforcement Learning Framework for Traffic Allocation in E-Commerce Search
Peng Cheng, Huimu Wang, Jinyuan Zhao +8
Traffic allocation is a process of redistributing natural traffic to products by adjusting their positions in the post-search phase, aimed at effectively fostering merchant growth,…