Efficient Semantic Enrichment Process for Spatiotemporal Trajectories

The increasing availability of location-acquisition technologies has enabled collecting large-scale spatiotemporal trajectories, from which we can derive semantic information in urban environments, including location, time, direction, speed, and point of interest. Such semantic information can give...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Bin Zhao, Mingyu Liu, Jingjing Han, Genlin Ji, Xintao Liu
Formato: article
Lenguaje:EN
Publicado: Hindawi-Wiley 2021
Materias:
T
Acceso en línea:https://doaj.org/article/ada9a3b2e3754584934f9b51c82b4267
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Descripción
Sumario:The increasing availability of location-acquisition technologies has enabled collecting large-scale spatiotemporal trajectories, from which we can derive semantic information in urban environments, including location, time, direction, speed, and point of interest. Such semantic information can give us a semantic interpretation of movement behaviors of moving objects. However, existing semantic enrichment process approaches, which can produce semantic trajectories, are generally time-consuming. In this paper, we propose an efficient semantic enrichment process framework to annotate spatiotemporal trajectories by using geographic and application domain knowledge. The framework mainly includes preannotated semantic trajectory storage phase, spatiotemporal similarity measurement phase, and semantic information matching phase. Having observed the common trajectories in the same geospatial object scenes, we propose a semantic information matching algorithm to match semantic information in preannotated semantic trajectories to new spatiotemporal trajectories. In order to improve the efficiency of this approach, we build a spatial index to enhance the preannotated semantic trajectories. Finally, the experimental results based on a real dataset demonstrate the effectiveness and efficiency of our proposed approaches.