The task of accurately forecasting the trajectory of a vessel, and in general a moving object
operating in free space until its destination remains an open challenge. This paper …

Trajectory clustering is an important operation of knowledge discovery from mobility data.
Especially nowadays, the need for performing advanced analytic operations over massively …

When COVID-19 first struck the provinces of Northern Italy in early 2020 (especially in
Lombardy and in Emilia-Romagna), the conditions there made it a perfect storm. The virus …

Sub-trajectory clustering is a fundamental problem in many trajectory applications. Existing
approaches usually divide the clustering procedure into two phases: segmenting trajectories …

With real time vessel surveillance data now becoming available at an increasing rate, there
is a growing interest in applications that can forecast future vessel positions and routes …

Given the widespread use of mobile devices that track their geographical location, it has
become increasingly easy to acquire information related to users' trips in real time. This …

Deployment and management of large-scale mobile edge computing infrastructure in 5G
networks has created a major challenge for mobile operators. The ability to extract common …

Trajectory representation learning on a network enhances our understanding of vehicular
traffic patterns and benefits numerous downstream applications. Existing approaches using …

In recent years, there has been observed an “explosion” of trajectory data production due to
the proliferation of GPS-enabled devices, such as mobile phones and tablets. This massive …

The unprecedented rate of trajectory data generation that has been observed during the
recent years, caused by the proliferation of GPS-enabled devices, poses new challenges in …