Mercury: Metro density prediction with recurrent neural network on streaming CDR data

@article{Liang2016MercuryMD,
  title={Mercury: Metro density prediction with recurrent neural network on streaming CDR data},
  author={Victor C. Liang and Richard T. B. Ma and Wee Siong Ng and Li Wang and Marianne Winslett and Huayu Wu and Shanshan Ying and Zhenjie Zhang},
  journal={2016 IEEE 32nd International Conference on Data Engineering (ICDE)},
  year={2016},
  pages={1374-1377}
}
Telecommunication companies possess mobility information of their phone users, containing accurate locations and velocities of commuters travelling in public transportation system. Although the value of telecommunication data is well believed under the smart city vision, there is no existing solution to transform the data into actionable items for better transportation, mainly due to the lack of appropriate data utilization scheme and the limited processing capability on massive data. This… CONTINUE READING

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