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Taxi Trajectories
DATA 004

Taxi Trajectories

Beijing City Lab Data

Type & Source Provided by MSRA (data downloadable at MSRA's website as follows) T-Drive Taxi Trajectorie s: This is a sample of T-Drive taxi trajectory dataset which was generated by over 10,000 taxis in a period of one week in Beijing. GeoLife Trajectory Dataset : This is a GPS trajectory dataset collected in (Microsoft Research Asia) GeoLife project by 167 users in a period of over two years (from April 2007 to Dec. 2010). This trajectory dataset can be used for many research themes, such as mobility pattern mining, user activity recognition, location-based social networks, location privacy, and location recomm...

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Taxi Trajectories
Taxi Trajectories
Taxi Trajectories
Taxi Trajectories
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Type & Source

Provided by MSRA (data downloadable at MSRA's website as follows)

  1. T-Drive Taxi Trajectories: This is a sample of T-Drive taxi trajectory dataset which was generated by over 10,000 taxis in a period of one week in Beijing.
  2. GeoLife Trajectory Dataset: This is a GPS trajectory dataset collected in (Microsoft Research Asia)GeoLife project by 167 users in a period of over two years (from April 2007 to Dec. 2010). This trajectory dataset can be used for many research themes, such as mobility pattern mining, user activity recognition, location-based social networks, location privacy, and location recommendation.


Citation

Yuan, J., Zheng, Y., Zhang, C., Xie, W., Xie, X., Sun, G. & Huang, Y. (2010). T-Drive: Driving directions based on taxi trajectories. Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems, 99–108. https://doi.org/10.1145/1869790.1869807. Zheng, Y., Zhang, L., Xie, X. & Ma, W.-Y. (2009). Mining interesting locations and travel sequences from GPS trajectories. Proceedings of WWW ’09, 791–800. https://doi.org/10.1145/1526709.1526816.

Access & Documentation

https://www.microsoft.com/en-us/download/details.aspx?id=52367

https://www.microsoft.com/en-us/research/project/geolife-building-social-networks-using-human-location-history/

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