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Genigraphics Research Poster Template 36x48T-drive: enhancing driving directions with taxi...
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Dong Wang Duke University Email: [email protected] Website: https://jelly007.github.io/ Contact 1. Wang, H.; Kuo, Y.-H.; Kifer, D.; and Li, Z. A simple baseline for travel time estimation using large-scale trip data. In Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 61. ACM. 2. Wang, Y.; Zheng, Y.; and Xue, Y. 2014. Travel time estimation of a path using sparse trajectories. In Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, 25–34. ACM. 3. Yang, B.; Guo, C.; and Jensen, C. S. 2013. Travel cost inference from sparse, spatio temporally correlated time series using markov models. Proceedings of the VLDB Endowment 6(9):769–780. 4. Yuan, J.; Zheng, Y.; Xie, X.; and Sun, G. 2013. T-drive: enhancing driving directions with taxi drivers’ intelligence. Knowledge and Data Engineering, IEEE Transactions on 25(1):220–232. 5. Zhang, J.; Zheng, Y.; and Qi, D. 2017. Deep spatio-temporal residual networks for citywide crowd flows prediction. In AAAI, 1655–1661. 6. Wang, D.; Cao, W.; Ye, P.; and Li, J. DeepSD: supply-demand prediction for online car-hailing services using deep neural networks. In Data Engineering (ICDE), 2017 IEEE 33rd International Conference on. References h 1 h 2 h 1 h 2 h n Softmax Layer h n α 1 α 2 α n Addit ion copy Wei Cao Tsinghua University Email: [email protected] Website: https://caow13.github.io/ Code
Transcript of Genigraphics Research Poster Template 36x48T-drive: enhancing driving directions with taxi...
Dong WangDuke UniversityEmail: [email protected]: https://jelly007.github.io/
Contact1. Wang, H.; Kuo, Y.-H.; Kifer, D.; and Li, Z. A simple baseline for travel time estimation using large-scale trip data. In Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic
Information Systems, 61. ACM.2. Wang, Y.; Zheng, Y.; and Xue, Y. 2014. Travel time estimation of a path using sparse trajectories. In Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, 25–34.
ACM.3. Yang, B.; Guo, C.; and Jensen, C. S. 2013. Travel cost inference from sparse, spatio temporally correlated time series using markov models. Proceedings of the VLDB Endowment 6(9):769–780. 4. Yuan, J.; Zheng, Y.; Xie, X.; and Sun, G. 2013. T-drive: enhancing driving directions with taxi drivers’ intelligence. Knowledge and Data Engineering, IEEE Transactions on 25(1):220–232.5. Zhang, J.; Zheng, Y.; and Qi, D. 2017. Deep spatio-temporal residual networks for citywide crowd flows prediction. In AAAI, 1655–1661. 6. Wang, D.; Cao, W.; Ye, P.; and Li, J. DeepSD: supply-demand prediction for online car-hailing services using deep neural networks. In Data Engineering (ICDE), 2017 IEEE 33rd International Conference on.
References
h1 h2
h1
h2
hn
Softmax Layer
hn
α1 α2 αn
Addit ion
copy
Wei CaoTsinghua UniversityEmail: [email protected]: https://caow13.github.io/
Code
