Searching Trajectories by Regions of Interest

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

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

1 Citation (Scopus)

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
Title of host publicationProceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018
Number of pages2
Publication date24 Oct 2018
Pages1741-1742
Article number8509449
ISBN (Print)978-1-5386-5520-7
ISBN (Electronic)9781538655207
DOIs
Publication statusPublished - 24 Oct 2018
Event34th IEEE International Conference on Data Engineering, ICDE 2018 - Paris, France
Duration: 16 Apr 201819 Apr 2018

Conference

Conference34th IEEE International Conference on Data Engineering, ICDE 2018
CountryFrance
CityParis
Period16/04/201819/04/2018

Keywords

  • Spatial databases
  • Spatial density correlation
  • Spatial networks
  • Trajectory search by regions

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

Cite this