1 citations · 1 across the 4 of their papers we have counts for
4 papers
STContext: A Multifaceted Dataset for Developing Context-aware Spatio-temporal Crowd Mobility Prediction Models
Liyue Chen, Jiangyi Fang, Tengfei Liu +2
In smart cities, context-aware spatio-temporal crowd flow prediction (STCFP) models leverage contextual features (e.g., weather) to identify unusual crowd mobility patterns and enh…
Efficient User Sequence Learning for Online Services via Compressed Graph Neural Networks
Yucheng Wu, Liyue Chen, Yu Cheng +3
Learning representations of user behavior sequences is crucial for various online services, such as online fraudulent transaction detection mechanisms. Graph Neural Networks (GNNs)…
A Unified Model for Spatio-Temporal Prediction Queries with Arbitrary Modifiable Areal Units
Liyue Chen, Jiangyi Fang, Tengfei Liu +2
Spatio-Temporal (ST) prediction is crucial for making informed decisions in urban location-based applications like ride-sharing. However, existing ST models often require region pa…
UCTB: An Urban Computing Tool Box for Building Spatiotemporal Prediction Services
Jiangyi Fang, Liyue Chen, Di Chai +4
Spatiotemporal crowd flow prediction is one of the key technologies in smart cities. Currently, there are two major pain points that plague related research and practitioners. Firs…