7 accepted papers
Inferring latent social ties from large-scale spatiotemporal mobility traces is a foundational AI task with broad applicability. Existing hypergraph-based methods often model higher-order relations by treating hyperedges as static snapshots, thus failing to capture the temporal dynamics and co-evolu
With the widespread use of location-tracking technologies, large volumes of trajectory data are continuously generated. Trajectory similarity computation is a core task in trajectory mining with broad applications. However, existing methods still face two key challenges: (1) the difficulty of balanc
Multivariate time series forecasting is a critical focus across many fields. Existing transformer-based models have overlooked the explicit modeling of inter-variable correlations. Similarly, the graph-based methods have also failed to address the dynamic nature of multivariate correlations and the
Trajectory-user linking (TUL) aims to match anonymous trajectories to the most likely users who generated them, offering benefits for a wide range of real-world spatio-temporal applications. However, existing TUL methods are limited by high model complexity and poor learning of the effective represe…
Traffic prediction is critical for optimizing travel scheduling and enhancing public safety, yet the complex spatial and temporal dynamics within traffic data present significant challenges for accurate forecasting. In this paper, we introduce a novel model, the Spatiotemporal-aware Trend-Seasonalit…
Inferring social relationships from human mobility data holds significant value in real-life spatio-temporal applications, which inspires the development of a series of graph-based methods for inferring social relationships. Despite their effectiveness, we argue that previous methods either rely sol…
Many efforts are devoted to predicting congestion evolution using propagation patterns that are mined from historical traffic data. However, the prediction quality is limited to the intrinsic properties that are present in the mined patterns. In addition, these mined patterns frequently fail to suf…