Due to the surge of spatio-temporal data volume, the popularity of location-based services
and applications, and the importance of extracted knowledge from spatio-temporal data to …

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

Every day, our living city produces a tremendous amount of spatial-temporal data, involved
with multiple sources from the individual scale to the city scale. Undoubtedly, such massive …

With the rapid evolution of the Internet, Internet of Things (IoT), and geographic information
systems (GIS), spatio-temporal Big Data (STBD) is experiencing exponential growth …

There are a prohibitively large number of floating-point time series data generated at an
unprecedentedly high rate. An efficient, compact and lossless compression for time series …

Similarity search has recently become an integral part of many trajectory data analysis tasks.
As the number of trajectories increases, we must find similar trajectories among massive …

With the explosive ubiquity of GPS-equipped devices, eg, mobile phones, vehicles, and
vessels, a massive amount of real-time, unbounded, and varying-sampling trajectory …

There are a prohibitively large number of floating-point time series data generated at an
unprecedentedly high rate. An efficient, compact and lossless compression for time series …

Due to the urgent demand for managing massive spatial data, various spatial data
management systems built on distributed NoSQL databases have emerged. However …

The effective management of trajectory data heavily relies on the utilization of fundamental
spatio-temporal queries. The surge in trajectory data, with its dynamic spatio-temporal …