51 citations · 104 across the 4 of their papers we have counts for
4 papers · 1 filter
Efficient Long Sequential User Data Modeling for Click-Through Rate Prediction
Qiwei Chen, Yue Xu, Changhua Pei +3
Recent studies on Click-Through Rate (CTR) prediction has reached new levels by modeling longer user behavior sequences. Among others, the two-stage methods stand out as the state-…
End-to-End User Behavior Retrieval in Click-Through RatePrediction Model
Qiwei Chen, Changhua Pei, Shanshan Lv +3
Click-Through Rate (CTR) prediction is one of the core tasks in recommender systems (RS). It predicts a personalized click probability for each user-item pair. Recently, researcher…
Behavior Sequence Transformer for E-commerce Recommendation in Alibaba
Qiwei Chen, Huan Zhao, Wei Li +2
Deep learning based methods have been widely used in industrial recommendation systems (RSs). Previous works adopt an Embedding&MLP paradigm: raw features are embedded into low-dim…
Multi-Interest Network with Dynamic Routing for Recommendation at Tmall
Chao Li, Zhiyuan Liu, Mengmeng Wu +7
Industrial recommender systems usually consist of the matching stage and the ranking stage, in order to handle the billion-scale of users and items. The matching stage retrieves ca…