Network-wide Crowd Flow Prediction of Sydney Trains via Customized Online Non-negative Matrix Factorization-Reference-Cited by-同舟云学术

Network-wide Crowd Flow Prediction of Sydney Trains via Customized Online Non-negative Matrix Factorization

Published:2018-10-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 27th ACM International Conference on Information and Knowledge Management
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Author:

Gong Yongshun¹,Li Zhibin¹,Zhang Jian¹,Liu Wei¹,Zheng Yu²,Kirsch Christina³

Affiliation:

1. University of Technology, Sydney, Sydney, Australia

2. JD Finance, Beijing, Beijing, China

3. Sydney Trains-Operational Technology, Sydney, Australia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3269206.3271757

Reference31 articles.

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2. Mathieu Blondel Yotaro Kubo and Ueda Naonori. 2014. Online passive-aggressive algorithms for non-negative matrix factorization and completion. In Artificial Intelligence and Statistics . 96--104. Mathieu Blondel Yotaro Kubo and Ueda Naonori. 2014. Online passive-aggressive algorithms for non-negative matrix factorization and completion. In Artificial Intelligence and Statistics . 96--104.

3. Detect and Track Latent Factors with Online Nonnegative Matrix Factorization;Cao Bin;IJCAI,2007

4. Avoiding the crowds

5. Exploring time variants for short-term passenger flow

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