Citywide traffic congestion estimation with social media-Reference-Cited by-同舟云学术

Citywide traffic congestion estimation with social media

Published:2015-11-03 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems
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Author:

Wang Senzhang¹,He Lifang²,Stenneth Leon³,Yu Philip S.⁴,Li Zhoujun¹

Affiliation:

1. Beihang University, Beijing, China

2. Shenzhen University, Shenzhen, China

3. Nokia's HERE Connected Driving, Chicago, IL

4. University of Illinois at Chicago, Chicago, IL

Funder

Fund of the State Key Laboratory of Software Development Environment

Pinnacle Lab at Singapore Management University

National High Technology Research and Development Program of China

Microsoft Research Asia Fund

Google Research Award

National Nature Science Foundation of China

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/2820783.2820829

Reference24 articles.

1. Mining Frequent Spatio-Temporal Sequential Patterns

2. Road Traffic Congestion Monitoring in Social Media with Hinge-Loss Markov Random Fields

3. Westland row why so slow?

4. E. D'Andrea P. Ducange B. Lazzerini and F. Marcelloni. Real-time detection of traffic from twitter stream analysis. Intelligent Transportation Systems PP(99):1--15 2015. E. D'Andrea P. Ducange B. Lazzerini and F. Marcelloni. Real-time detection of traffic from twitter stream analysis. Intelligent Transportation Systems PP(99):1--15 2015.

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