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2018 IEEE 34th International Conference on Data Engineering (ICDE) (2018)
Paris, France
Apr 16, 2018 to Apr 19, 2018
ISSN: 2375-026X
ISBN: 978-1-5386-5520-7
pp: 1741-1742
We propose and investigate a novel query type named trajectory search by regions of interest (TSR query). Given an argument set of trajectories, a TSR query takes a set of regions of interest as a parameter and returns the trajectory in the argument set with the highest spatial-density correlation to the query regions. This type of query is useful in applications such as trip planning and recommendation. To process the TSR query, a set of new metrics are defined to model spatial-density correlations. An efficient trajectory search algorithm is developed that exploits upper and lower bounds to prune the search space and that adopts a query-source selection strategy, as well as integrates a heuristic search strategy based on priority ranking to schedule multiple query sources. The performance of TSR query processing is studied in extensive experiments based on real and synthetic spatial data.
query processing, scheduling, search problems

S. Shang, L. Chen, C. S. Jensen, J. Wen and P. Kalnis, "Searching Trajectories by Regions of Interest," 2018 IEEE 34th International Conference on Data Engineering (ICDE), Paris, France, 2018, pp. 1741-1742.
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