21 citations · 24 across the 11 of their papers we have counts for
5 papers · 1 filter
Towards Principled Learning for Re-ranking in Recommender Systems
Qunwei Li, Linghui Li, Jianbin Lin +1
As the final stage of recommender systems, re-ranking presents ordered item lists to users that best match their interests. It plays such a critical role and has become a trending…
Denoising Time Cycle Modeling for Recommendation
Sicong Xie, Qunwei Li, Weidi Xu +3
Recently, modeling temporal patterns of user-item interactions have attracted much attention in recommender systems. We argue that existing methods ignore the variety of temporal p…
PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation
Chunjing Gan, Bo Huang, Binbin Hu +6
To help merchants/customers to provide/access a variety of services through miniapps, online service platforms have occupied a critical position in the effective content delivery,…
AntMC: A Large Scale Dataset For Multi-Scenario Multi-Modal CTR Prediction
Zhaoxin Huan, Ke Ding, Ang Li +10
Click-through rate (CTR) prediction is a crucial issue in recommendation systems. There has been an emergence of various public CTR datasets. However, existing datasets primarily s…
COUPA: An Industrial Recommender System for Online to Offline Service Platforms
Sicong Xie, Binbin Hu, Fengze Li +4
Aiming at helping users locally discovery retail services (e.g., entertainment and dinning), Online to Offline (O2O) service platforms have become popular in recent years, which gr…