Parallel Subtrajectory Alignment over Massive-Scale Trajectory Data

Chen, Lisi; Shang, Shuo; Feng, Shanshan; Kalnis, Panos

doi:10.24963/ijcai.2021/497

Parallel Subtrajectory Alignment over Massive-Scale Trajectory Data

Lisi Chen, Shuo Shang, Shanshan Feng, Panos Kalnis

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Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. Main Track. Pages 3613-3619.

https://doi.org/10.24963/ijcai.2021/497

Keywords

Multidisciplinary Topics and Applications: Transportation
Data Mining: Mining Spatial, Temporal Data

Abstract

We study the problem of subtrajectory alignment over massive-scale trajectory data. Given a collection of trajectories, a subtrajectory alignment query returns new targeted trajectories by splitting and aligning existing trajectories. The resulting functionality targets a range of applications, including trajectory data analysis, route planning and recommendation, ridesharing, and general location-based services. To enable efficient and effective subtrajectory alignment computation, we propose a novel search algorithm and filtering techniques that enable the use of the parallel processing capabilities of modern processors. Experiments with large trajectory datasets are conducted for evaluating the performance of our proposal. The results show that our solution to the subtrajectory alignment problem can generate high-quality results and are capable of achieving high efficiency and scalability.

Lisi Chen, Shuo Shang, Shanshan Feng, and Panos Kalnis. 2021. Parallel Subtrajectory Alignment over Massive-Scale Trajectory Data. In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21. IJCAI, 3613–3619. https://doi.org/10.24963/ijcai.2021/497

@inproceedings{ijcai2021p497,
  title     = {Parallel Subtrajectory Alignment over Massive-Scale Trajectory Data},
  author    = {Chen, Lisi and Shang, Shuo and Feng, Shanshan and Kalnis, Panos},
  booktitle = {Proceedings of the Thirtieth International Joint Conference on
               Artificial Intelligence, {IJCAI-21}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Prof. Zhi-Hua Zhou},
  pages     = {3613--3619},
  year      = {2021},
  month     = {8},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2021/497},
  url       = {https://doi.org/10.24963/ijcai.2021/497},
}

TY  - CPAPER
TI  - Parallel Subtrajectory Alignment over Massive-Scale Trajectory Data
AU  - Chen, Lisi
AU  - Shang, Shuo
AU  - Feng, Shanshan
AU  - Kalnis, Panos
T2  - Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2021
SP  - 3613
EP  - 3619
DO  - 10.24963/ijcai.2021/497
UR  - https://doi.org/10.24963/ijcai.2021/497
ER  -