Searching Trajectories by Regions of Interest

Shuo Shang, Lisi Chen, Christian S. Jensen, Ji-Rong Wen, Panos Kalnis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

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.
Original languageEnglish (US)
Title of host publication2018 IEEE 34th International Conference on Data Engineering (ICDE)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1741-1742
Number of pages2
ISBN (Print)9781538655207
DOIs
StatePublished - Oct 25 2018

Fingerprint

Dive into the research topics of 'Searching Trajectories by Regions of Interest'. Together they form a unique fingerprint.

Cite this