172 citations · 339 across the 8 of their papers we have counts for
8 papers
Cross-city Few-Shot Traffic Forecasting via Traffic Pattern Bank
Zhanyu Liu, Guanjie Zheng, Yanwei Yu
Traffic forecasting is a critical service in Intelligent Transportation Systems (ITS). Utilizing deep models to tackle this task relies heavily on data from traffic sensors or vehi…
Trajectory-User Linking via Hierarchical Spatio-Temporal Attention Networks
Wei Chen, Chao Huang, Yanwei Yu +2
Trajectory-User Linking (TUL) is crucial for human mobility modeling by linking diferent trajectories to users with the exploration of complex mobility patterns. Existing works mai…
Multiplex Heterogeneous Graph Convolutional Network
Pengyang Yu, Chaofan Fu, Yanwei Yu +3
Heterogeneous graph convolutional networks have gained great popularity in tackling various network analytical tasks on heterogeneous network data, ranging from link prediction to…
Online Discovery of Evolving Groups over Massive-Scale Trajectory Streams
Yanwei Yu, Ruoshan Lan, Lei Cao +2
The increasing pervasiveness of object tracking technologies leads to huge volumes of spatiotemporal data collected in the form of trajectory streams. The discovery of useful group…
Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation
Yuhao Yang, Chao Huang, Lianghao Xia +3
Learning dynamic user preference has become an increasingly important component for many online platforms (e.g., video-sharing sites, e-commerce systems) to make sequential recomme…
Mutual Distillation Learning Network for Trajectory-User Linking
Wei Chen, Shuzhe Li, Chao Huang +3
Trajectory-User Linking (TUL), which links trajectories to users who generate them, has been a challenging problem due to the sparsity in check-in mobility data. Existing methods i…
Scalable Motif Counting for Large-scale Temporal Graphs
Zhongqiang Gao, Chuanqi Cheng, Yanwei Yu +3
One fundamental problem in temporal graph analysis is to count the occurrences of small connected subgraph patterns (i.e., motifs), which benefits a broad range of real-world appli…
Joint Modeling of Dense and Incomplete Trajectories for Citywide Traffic Volume Inference
Xianfeng Tang, Boqing Gong, Yanwei Yu +4
Real-time traffic volume inference is key to an intelligent city. It is a challenging task because accurate traffic volumes on the roads can only be measured at certain locations w…