Time series analysis stands as a focal point within the data mining community, serving as a
cornerstone for extracting valuable insights crucial to a myriad of real-world applications …

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

The proliferation of trajectory data has facilitated various applications in urban spaces, such
as travel time estimation, traffic monitoring, and flow prediction. These applications require a …

Computing trajectory similarity plays a critical role in various spatio-temporal applications
that involve trajectory analysis. In recent years, trajectory representation learning has been …

The proliferation of geospatial data in urban and territorial environments has significantly
facilitated the development of geospatial artificial intelligence (GeoAI) across various urban …

The dynamic correlation analysis of cell-spatial information (distributed anode current signal,
DACS) is of great significance in the regional-refined control of industrial aluminum …

An increasing number of related urban data sources have brought forth novel opportunities
for learning urban region representations, ie, embeddings. The embeddings describe latent …

Vehicle trajectories provide valuable movement information that supports various
downstream tasks and powers real-world applications. A desirable trajectory learning model …

Spatiotemporal trajectories are sequences of timestamped locations, which enable a variety
of analyses that in turn enable important real-world applications. It is common to map …

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