Abstract
In this paper, we define a new measure to compute spatio-temporal similarity between two trajectories of moving objects on road networks, which is known as spatio-temporal distance (STDist). In addition, we propose a new spatio-temporal similar trajectory search algorithm to retrieve similar trajectories based on the spatio-temporal distance, a combination of both spatial and temporal properties with respect to the motion of a given query trajectory. To support fast trajectories retrieval, we use a signature file method in which we generate signatures for segments of a trajectory. Our performance analysis shows that our algorithm outperforms the existing method in terms of searching similar trajectories of moving objects on road network.
| Original language | English |
|---|---|
| Title of host publication | CIT 2007 |
| Subtitle of host publication | 7th IEEE International Conference on Computer and Information Technology |
| Pages | 110-115 |
| Number of pages | 6 |
| DOIs | |
| State | Published - 2007 |
| Event | CIT 2007: 7th IEEE International Conference on Computer and Information Technology - Aizu-Wakamatsu, Fukushima, Japan Duration: 2007.10.16 → 2007.10.19 |
Publication series
| Name | CIT 2007: 7th IEEE International Conference on Computer and Information Technology |
|---|
Conference
| Conference | CIT 2007: 7th IEEE International Conference on Computer and Information Technology |
|---|---|
| Country/Territory | Japan |
| City | Aizu-Wakamatsu, Fukushima |
| Period | 07.10.16 → 07.10.19 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Quacquarelli Symonds(QS) Subject Topics
- Computer Science & Information Systems
- Mathematics
- Data Science
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