Trajectory computing is a pivotal domain encompassing trajectory data management and
mining, garnering widespread attention due to its crucial role in various practical …

Trajectories that capture object movement have numerous applications, in which similarity
computation between trajectories often plays a key role. Traditionally, trajectory similarity is …

Trajectory representation learning aims to embed trajectory sequences into fixed-length
vector representations while preserving their original spatio-temporal feature proximity …

Urban mobility analysis has been extensively studied in the past decade using a vast
amount of GPS trajectory data, which reveals hidden patterns in movement and human …

Trajectory-User Linking (TUL) aiming to identify users of anonymous trajectories, has
recently received increasing attention due to its wide range of applications, such as criminal …

With the increasing popularity of wireless networks and the development of smart cities, the
Mobile Crowdsourcing System (MCS) has emerged as a framework for automatically …

Trajectory anomaly detection, aiming to estimate the anomaly risk of trajectories given the
Source-Destination (SD) pairs, has become a critical problem for many real-world …

Trajectory similarity computation serves as a fundamental functionality of various spatial
information applications. Although existing deep learning similarity computation methods …

With the increasing popularity of automatic identification system AIS devices, mining latent
vessel motion patterns from AIS data has become a hot topic in water transportation …

Spatial trajectory prediction is a fundamental problem for diverse location-based
applications. However, existing methods fall short in learning and generalization, and …