Multiple-Aspect Analysis of Semantic Trajectories
Editorial: Springer Nature
Licencia: Creative Commons (by)
Autor(es): Tserpes, Konstantinos; [et al.]
An ever-increasing number of diverse, real-life applications, ranging from mobile to
social media apps and surveillance systems, produce massive amounts of
spatio-temporal data representing trajectories of moving objects. The fusion of those
trajectories, commonly represented by timestamped location sequence data (e.g.
check-ins and GPS traces), with generally available and semantic-rich data resources
can result in an enriched set of more comprehensive and semantically significant
objects. The analysis of these sets, referred to as "semantic trajectories", can unveil
solutions to traditional problems and unlock the challenges for the advent of novel
applications and application domains, such as transportation, security, health, environment, and even policy modeling.
[Cham: 2020]
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