COUPA: An Industrial Recommender System for Online to Offline Service Platforms

Sicong Xie, Binbin Hu, Fengze Li, Ziqi Liu, Zhiqiang Zhang, Wenliang Zhong, Jun Zhou

Abstract: Aiming at helping users locally discover retail services (e.g., entertainment and dining) on Online to Offline (O2O) service platforms, we propose COUPA, an industrial system targeting for characterizing user preference with inspiring considerations of time and position aware preferences. We carefully implement and deploy COUPA in Alipay with a cooperation of edge, streaming and batch computing, as well as a two-stage online serving mode, to support several popular recommendation scenarios. Extensive experiments reveal the superior performance of COUPA for recommendation.