The simpler the better: A unified approach to predicting original taxi demands on large-scale online platforms

Author

Yongxin TONG
Yuqiang CHEN
Zimu ZHOU, Singapore Management UniversityFollow
Lei CHEN
Jie WANG
Qiang YANG
Jieping YE
Weifeng LV

Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

8-2017

Keywords

Unit Original Taxi Demands, Prediction, Feature Engineering

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, Canada, 2017 August 13-17

First Page

1653

Last Page

1662

Identifier

10.1145/3097983.3098018

Publisher

ACM

City or Country

Halifax, Canada

Citation

TONG, Yongxin; CHEN, Yuqiang; ZHOU, Zimu; CHEN, Lei; WANG, Jie; YANG, Qiang; YE, Jieping; and LV, Weifeng. The simpler the better: A unified approach to predicting original taxi demands on large-scale online platforms. (2017). Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, Canada, 2017 August 13-17. 1653-1662.
Available at: https://ink.library.smu.edu.sg/sis_research/4740

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.

Additional URL

https://doi.org/10.1145/3097983.3098018