Hybrid Queries over Symbolic and Spatial Trajectories: A Usage Scenario

Abstract

Symbolic trajectories is a novel data model recently proposed for the modeling and querying of temporally annotated sequences of symbolic descriptions, representing e.g. transportation means, places of interest, and so forth. Unlike geometric trajectories, symbolic trajectories capture the thematic dimension of movement. In this demonstration, we illustrate a practical approach to the querying of hybrid trajectories, combining the symbolic and geometric dimension in a multidimensional trajectory. The system runs on the Secondo moving object database. The multi-dimensional trajectories are obtained from the GeoLife dataset.

A topological model of trajectories with road network space

“…Recently, there has been a surge in semantic enrichment (Zheng, 2015) with GPS trajectory data. Many studies have described semantic information from moving object data, including stop‐and‐move models (Damiani & Güting, 2014; Parent, Pelekis, Theodoridis, & Yan, 2013; Spaccapietra & Parent, 2011), time‐dependent‐label models (Damiani, Issa, Guting, & Valdes, 2014; Güting, Valdés, & Damiani, 2015; Renso, Baglioni, de Macedo, Trasarti, & Wachowicz, 2013), location‐correlation (Cai, Lee, & Lee, 2018; Valdés, Damiani, & Güting, 2013; Yan, 2011), and other hybrid methods (Issa, 2016; Wan, Zhou and Pei, 2017). Among these methods, raw trajectories are divided into sequences of subtrajectories that meet prescribed spatiotemporal thresholds, and semantic annotations are generated by a wide range of methods, such as clustering (Cai, 2017; Hung, Peng, & Lee, 2015; Yuan, Sun, Zhao, & Li, Wang, 2017), manual annotations (Cai, 2017; Nabo, Fileto, Nanni, & Renso, 2014), and spatial correlation methods (Renso et al, 2013; Wang & Kwan, 2018).…”

Symbolic trajectories and application challenges

“…Rather a tighter integration of the trajectories representations, both at language and system level, is needed. A first approach to the problem has been shown in [4]. The idea is to leverage the temporal correlation between the two trajectories by retrieving the sub-trajectories which match the symbolic pattern and, based on them, temporally restrict the spatial trajectories.…”

Semantic Trajectories and Beyond

“…On the other hand, there are numerous research issues that are still open. In particular the notion of symbolic trajectories opens up several challenges, such as the integration of the symbolic dimension with the geometric dimension to achieve multi-dimensional trajectories [16], the deployment of the concept in advanced applications, and the integration with large scale data analytical techniques (e.g. trajectory data warehouses, data mining).…”