17 citations · 36 across the 6 of their papers we have counts for
4 papers · 1 filter
Rethinking Large-scale Pre-ranking System: Entire-chain Cross-domain Models
Jinbo Song, Ruoran Huang, Xinyang Wang +9
Industrial systems such as recommender systems and online advertising, have been widely equipped with multi-stage architectures, which are divided into several cascaded modules, in…
Towards Better Query Classification with Multi-Expert Knowledge Condensation in JD Ads Search
Kun-Peng Ning, Ming Pang, Zheng Fang +6
Search query classification, as an effective way to understand user intents, is of great importance in real-world online ads systems. To ensure a lower latency, a shallow model (e.…
Always Strengthen Your Strengths: A Drift-Aware Incremental Learning Framework for CTR Prediction
Congcong Liu, Fei Teng, Xiwei Zhao +3
Click-through rate (CTR) prediction is of great importance in recommendation systems and online advertising platforms. When served in industrial scenarios, the user-generated data…
Telepath: Understanding Users from a Human Vision Perspective in Large-Scale Recommender Systems
Yu Wang, Jixing Xu, Aohan Wu +4
Designing an e-commerce recommender system that serves hundreds of millions of active users is a daunting challenge. From a human vision perspective, there're two key factors that…