5 citations · 8 across the 4 of their papers we have counts for
4 papers
CanniUplift: A Holistic Framework for Mitigating Seller and Incentive Cannibalization in E-commerce Uplift Modeling
Zuwang He, Shihao Shu, Yuli Qu +8
Personalized incentive allocation is vital for e-commerce, where uplift modeling is the standard for estimating Individual Treatment Effects (ITE). However, traditional models ofte…
Single-Layer Graph Convolutional Networks For Recommendation
Yue Xu, Hao Chen, Zengde Deng +5
Graph Convolutional Networks (GCNs) and their variants have received significant attention and achieved start-of-the-art performances on various recommendation tasks. However, many…
Query-based Interactive Recommendation by Meta-Path and Adapted Attention-GRU
Yu Zhu, Yu Gong, Qingwen Liu +6
Recently, interactive recommender systems are becoming increasingly popular. The insight is that, with the interaction between users and the system, (1) users can actively interven…
A Brand-level Ranking System with the Customized Attention-GRU Model
Yu Zhu, Junxiong Zhu, Jie Hou +4
In e-commerce websites like Taobao, brand is playing a more important role in influencing users' decision of click/purchase, partly because users are now attaching more importance…