5 papers
Mitigating Recommendation Biases via Group-Alignment and Global-Uniformity in Representation Learning
Miaomiao Cai, Min Hou, Lei Chen +4
Collaborative Filtering~(CF) plays a crucial role in modern recommender systems, leveraging historical user-item interactions to provide personalized suggestions. However, CF-based…
Disentangled Interest Network for Out-of-Distribution CTR Prediction
Yu Zheng, Chen Gao, Jianxin Chang +5
Click-through rate (CTR) prediction, which estimates the probability of a user clicking on a given item, is a critical task for online information services. Existing approaches oft…
DeepSTA: A Spatial-Temporal Attention Network for Logistics Delivery Timely Rate Prediction in Anomaly Conditions
Jinhui Yi, Huan Yan, Haotian Wang +2
Prediction of couriers' delivery timely rates in advance is essential to the logistics industry, enabling companies to take preemptive measures to ensure the normal operation of de…
Learning to Estimate Package Delivery Time in Mixed Imbalanced Delivery and Pickup Logistics Services
Jinhui Yi, Huan Yan, Haotian Wang +2
Accurately estimating package delivery time is essential to the logistics industry, which enables reasonable work allocation and on-time service guarantee. This becomes even more n…
AppGen: Mobility-aware App Usage Behavior Generation for Mobile Users
Zihan Huang, Tong Li, Yong Li
Mobile app usage behavior reveals human patterns and is crucial for stakeholders, but data collection is costly and raises privacy issues. Data synthesis can address this by genera…