Optimal seeds discovery of traffic congestions |
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Author: | Bermejo, Carlos1; Wu, Ting1; Su, Xiang2,3; |
Organizations: |
1Department of Computer Science and Engineering, Hong Kong University of Science and Technology 2Department of Computer Science, University of Helsinki 3Department of Computer Science, University of Oulu |
Format: | article |
Version: | accepted version |
Access: | open |
Online Access: | PDF Full Text (PDF, 1.3 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe20201217101060 |
Language: | English |
Published: |
Institute of Electrical and Electronics Engineers,
2020
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Publish Date: | 2020-12-17 |
Description: |
AbstractWith the rapid adoption of wireless sensor networks (WSNs) into smart cities and vehicle networks, traffic problems can be evaluated and predicted in real-time. In this paper, we propose a data-driven approach to find out the most influential causes of traffic congestions. We first find the top most influential regions and use the Fortune’s algorithm to partition the city. Second, we propose a model with three correlations to measure the dependency between two traffic events, which are spatial correlation, temporal correlation, and logical correlation. Third, we adapt the Independent Cascade model with a pruning algorithm to address traffic congestions. At last, we conduct intensive experiments on large real-world GPS trajectories generated by more than 10,200 taxis in Shanghai to demonstrate the performance of our approaches. see all
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Series: |
IEEE International Conference on Data Engineering workshop |
ISSN: | 1943-2895 |
ISSN-E: | 2473-3490 |
ISSN-L: | 1943-2895 |
ISBN: | 978-1-7281-4266-1 |
ISBN Print: | 978-1-7281-4267-8 |
Pages: | 71 - 78 |
DOI: | 10.1109/ICDEW49219.2020.000-5 |
OADOI: | https://oadoi.org/10.1109/ICDEW49219.2020.000-5 |
Host publication: |
2020 IEEE 36th International Conference on Data Engineering Workshops (ICDEW) |
Conference: |
IEEE International Conference on Data Engineering Workshops |
Type of Publication: |
A4 Article in conference proceedings |
Field of Science: |
113 Computer and information sciences 213 Electronic, automation and communications engineering, electronics |
Subjects: | |
Copyright information: |
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