Forecasting Public Transit Use by Crowdsensing and Semantic Trajectory Mining: Case Studies

Ningyu Zhang, Huajun Chen, Xi Chen, Jiaoyan Chen

Open source

DOI: 10.3390/ijgi5100180
Published: 9
Container: ISPRS International Journal of Geo-Information
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3390/ijgi5100180,
  title = {Forecasting Public Transit Use by Crowdsensing and Semantic Trajectory Mining: Case Studies},
  author = {Ningyu Zhang and Huajun Chen and Xi Chen and Jiaoyan Chen},
  year = {2016},
  journal = {ISPRS International Journal of Geo-Information},
  doi = {10.3390/ijgi5100180},
  url = {https://doi.org/10.3390/ijgi5100180}
}

RIS

TY  - JOUR
TI  - Forecasting Public Transit Use by Crowdsensing and Semantic Trajectory Mining: Case Studies
AU  - Ningyu Zhang
AU  - Huajun Chen
AU  - Xi Chen
AU  - Jiaoyan Chen
PY  - 2016
JO  - ISPRS International Journal of Geo-Information
DO  - 10.3390/ijgi5100180
UR  - https://doi.org/10.3390/ijgi5100180
ER  -

APA

Zhang, N., Chen, H., Chen, X., & Chen, J. (2016). Forecasting Public Transit Use by Crowdsensing and Semantic Trajectory Mining: Case Studies. ISPRS International Journal of Geo-Information. https://doi.org/10.3390/ijgi5100180

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doaj · retrieved 2026-09-25T12:16:25.285Z