89 citations · 131 across the 10 of their papers we have counts for
4 papers · 2 filters
AT4CTR: Auxiliary Match Tasks for Enhancing Click-Through Rate Prediction
Qi Liu, Xuyang Hou, Defu Lian +4
Click-through rate (CTR) prediction is a vital task in industrial recommendation systems. Most existing methods focus on the network architecture design of the CTR model for better…
Deep Group Interest Modeling of Full Lifelong User Behaviors for CTR Prediction
Qi Liu, Xuyang Hou, Haoran Jin +6
Extracting users' interests from their lifelong behavior sequence is crucial for predicting Click-Through Rate (CTR). Most current methods employ a two-stage process for efficiency…
STGIN: Spatial-Temporal Graph Interaction Network for Large-scale POI Recommendation
Shaohua Liu, Yu Qi, Gen Li +4
In Location-Based Services, Point-Of-Interest(POI) recommendation plays a crucial role in both user experience and business opportunities. Graph neural networks have been proven ef…
Deep Context Interest Network for Click-Through Rate Prediction
Xuyang Hou, Zhe Wang, Qi Liu +3
Click-Through Rate (CTR) prediction, estimating the probability of a user clicking on an item, is essential in industrial applications, such as online advertising. Many works focus…