Deep representation learning for trajectory similarity computation

Xiucheng Li, Kaiqi Zhao, Gao Cong, Christian Søndergaard Jensen, Wei Wei

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

4 Citations (Scopus)
Original languageEnglish
Title of host publicationIEEE International Conference on Data Engineering (ICDE)
Number of pages12
PublisherIEEE
Publication date24 Oct 2018
Pages617-628
Article number8509283
ISBN (Print)978-1-5386-5520-7
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
SeriesProceedings of the International Conference on Data Engineering
ISSN1063-6382

Fingerprint

Trajectories
Animals
Sampling
Experiments

Keywords

  • Deep neural nets
  • representation learning
  • Trajectory similarity

Cite this

Li, X., Zhao, K., Cong, G., Jensen, C. S., & Wei, W. (2018). Deep representation learning for trajectory similarity computation. In IEEE International Conference on Data Engineering (ICDE) (pp. 617-628). [8509283] IEEE. Proceedings of the International Conference on Data Engineering https://doi.org/10.1109/ICDE.2018.00062
Li, Xiucheng ; Zhao, Kaiqi ; Cong, Gao ; Jensen, Christian Søndergaard ; Wei, Wei. / Deep representation learning for trajectory similarity computation. IEEE International Conference on Data Engineering (ICDE). IEEE, 2018. pp. 617-628 (Proceedings of the International Conference on Data Engineering).
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title = "Deep representation learning for trajectory similarity computation",
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author = "Xiucheng Li and Kaiqi Zhao and Gao Cong and Jensen, {Christian S{\o}ndergaard} and Wei Wei",
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doi = "10.1109/ICDE.2018.00062",
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Li, X, Zhao, K, Cong, G, Jensen, CS & Wei, W 2018, Deep representation learning for trajectory similarity computation. in IEEE International Conference on Data Engineering (ICDE)., 8509283, IEEE, Proceedings of the International Conference on Data Engineering, pp. 617-628, 34th IEEE International Conference on Data Engineering, ICDE 2018, Paris, France, 16/04/2018. https://doi.org/10.1109/ICDE.2018.00062

Deep representation learning for trajectory similarity computation. / Li, Xiucheng; Zhao, Kaiqi; Cong, Gao; Jensen, Christian Søndergaard; Wei, Wei.

IEEE International Conference on Data Engineering (ICDE). IEEE, 2018. p. 617-628 8509283.

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

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AU - Zhao, Kaiqi

AU - Cong, Gao

AU - Jensen, Christian Søndergaard

AU - Wei, Wei

PY - 2018/10/24

Y1 - 2018/10/24

KW - Deep neural nets

KW - representation learning

KW - Trajectory similarity

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U2 - 10.1109/ICDE.2018.00062

DO - 10.1109/ICDE.2018.00062

M3 - Article in proceeding

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BT - IEEE International Conference on Data Engineering (ICDE)

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Li X, Zhao K, Cong G, Jensen CS, Wei W. Deep representation learning for trajectory similarity computation. In IEEE International Conference on Data Engineering (ICDE). IEEE. 2018. p. 617-628. 8509283. (Proceedings of the International Conference on Data Engineering). https://doi.org/10.1109/ICDE.2018.00062