Abstract
| Original language | English |
|---|---|
| Title of host publication | Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018 |
| Number of pages | 2 |
| Publication date | 24 Oct 2018 |
| Pages | 1741-1742 |
| Article number | 8509449 |
| ISBN (Print) | 978-1-5386-5520-7 |
| ISBN (Electronic) | 9781538655207 |
| DOIs | |
| Publication status | Published - 24 Oct 2018 |
| Event | 34th IEEE International Conference on Data Engineering, ICDE 2018 - Paris, France Duration: 16 Apr 2018 → 19 Apr 2018 |
Conference
| Conference | 34th IEEE International Conference on Data Engineering, ICDE 2018 |
|---|---|
| Country | France |
| City | Paris |
| Period | 16/04/2018 → 19/04/2018 |
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Keywords
- Spatial databases
- Spatial density correlation
- Spatial networks
- Trajectory search by regions
Cite this
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Searching Trajectories by Regions of Interest. / Shang, Shuo ; Chen, Lisi; Jensen, Christian Søndergaard; Wen, Ji-Rong; Kalnis, Panos.
Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018. 2018. p. 1741-1742 8509449.Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review
TY - GEN
T1 - Searching Trajectories by Regions of Interest
AU - Shang, Shuo
AU - Chen, Lisi
AU - Jensen, Christian Søndergaard
AU - Wen, Ji-Rong
AU - Kalnis, Panos
PY - 2018/10/24
Y1 - 2018/10/24
N2 - 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.
AB - 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.
KW - Spatial databases
KW - Spatial density correlation
KW - Spatial networks
KW - Trajectory search by regions
UR - http://www.scopus.com/inward/record.url?scp=85057128114&partnerID=8YFLogxK
U2 - 10.1109/ICDE.2018.00228
DO - 10.1109/ICDE.2018.00228
M3 - Article in proceeding
SN - 978-1-5386-5520-7
SP - 1741
EP - 1742
BT - Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018
ER -